=2.7.3\n",
"\n",
"from datasets import Audio, interleave_datasets, IterableDataset, load_dataset\n",
"from typing import List, Optional\n",
"\n",
"dataset_names = [\"mozilla-foundation/common_voice_11_0\", \"google/fleurs\"]\n",
"dataset_config_names = [\"el\", \"el_gr\"]\n",
"text_column_names = [\"sentence\", \"transcription\"]\n",
"\n"
]
},
{
"cell_type": "markdown",
"id": "674429c5-0ab4-4adf-975b-621bb69eca38",
"metadata": {
"id": "674429c5-0ab4-4adf-975b-621bb69eca38"
},
"source": [
"We'll train our system on the Spanish split of [Common Voice 11](https://huggingface.co/datasets/mozilla-foundation/common_voice_11_0). We can see how much training data we have by viewing the [language page](https://commonvoice.mozilla.org/en/datasets) on the Common Voice website. The Spanish split has over 400 hours of labelled training data - that's enourmous! More than we could ever fit on a Google Colab or a standard workstation. But with streaming mode, we'll only download data as and when we need it, making training on this dataset possible!\n",
"\n",
"Since Spanish is relatively high-resource, we'll only use the `train` split for training and the `test` split for evaluation. If you're training on a low-resource language, such as the Hindi split of Common Voice 11, it's worth combining the `train` and `validation` splits to give a larger training set. You can achieve this by setting: `split=\"train+validation\"` for the training split.\n",
"\n",
"If you're using a gated dataset, like Common Voice 11, ensure you have accepted the terms of use on the Hugging Face Hub: [mozilla-foundation/common_voice_11_0](https://huggingface.co/datasets/mozilla-foundation/common_voice_11_0). Once you have accepted the terms, you will have full access to the dataset and be able to load the data locally."
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "a2787582-554f-44ce-9f38-4180a5ed6b44",
"metadata": {
"id": "a2787582-554f-44ce-9f38-4180a5ed6b44",
"tags": []
},
"outputs": [],
"source": [
"def load_multiple_streaming_datasets(\n",
" dataset_names: List,\n",
" dataset_config_names: List,\n",
" splits: Optional[List] = None,\n",
" text_column_names: Optional[List] = None,\n",
" sampling_rate: Optional[int] = 16000,\n",
" stopping_strategy: Optional[str] = \"all_exhausted\",\n",
" **kwargs\n",
") -> IterableDataset:\n",
"\n",
" if len(dataset_names) != len(dataset_config_names):\n",
" raise ValueError(\n",
" f\"Ensure one config is passed for each dataset, got {len(dataset_names)} datasets and\"\n",
" f\" {len(dataset_config_names)} configs.\"\n",
" )\n",
"\n",
" if splits is not None and len(splits) != len(dataset_names):\n",
" raise ValueError(\n",
" f\"Ensure one split is passed for each dataset, got {len(dataset_names)} datasets and {len(splits)} splits.\"\n",
" )\n",
"\n",
" if text_column_names is not None and len(text_column_names) != len(dataset_names):\n",
" raise ValueError(\n",
" f\"Ensure one text column name is passed for each dataset, got {len(dataset_names)} datasets and\"\n",
" f\" {len(text_column_names)} text column names.\"\n",
" )\n",
"\n",
" splits = splits if splits is not None else [\"train\" for i in range(len(dataset_names))]\n",
" text_column_names = (\n",
" text_column_names if text_column_names is not None else [\"text\" for i in range(len(dataset_names))]\n",
" )\n",
"\n",
" all_datasets = []\n",
" # iterate over the datasets we want to interleave\n",
" for i, dataset_name in enumerate(dataset_names):\n",
" dataset = load_dataset(dataset_name, dataset_config_names[i], split=splits[i], streaming=False, **kwargs)\n",
" # resample to specified sampling rate\n",
" dataset = dataset.cast_column(\"audio\", Audio(sampling_rate))\n",
" # normalise columns to [\"audio\", \"sentence\"]\n",
" if text_column_names[i] != \"sentence\":\n",
" dataset = dataset.rename_column(text_column_names[i], \"sentence\")\n",
" dataset = dataset.remove_columns(set(dataset.features.keys()) - set([\"audio\", \"sentence\"]))\n",
" all_datasets.append(dataset)\n",
"\n",
" interleaved_dataset = interleave_datasets(all_datasets, stopping_strategy=stopping_strategy)\n",
" return interleaved_dataset\n",
"\n",
"\n",
"\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "qOwlctMhNmCG",
"metadata": {
"id": "qOwlctMhNmCG",
"tags": []
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"Found cached dataset common_voice_11_0 (/home/ubuntu/.cache/huggingface/datasets/mozilla-foundation___common_voice_11_0/el/11.0.0/f8e47235d9b4e68fa24ed71d63266a02018ccf7194b2a8c9c598a5f3ab304d9f)\n",
"Found cached dataset fleurs (/home/ubuntu/.cache/huggingface/datasets/google___fleurs/el_gr/2.0.0/aabb39fb29739c495517ac904e2886819b6e344702f0a5b5283cb178b087c94a)\n"
]
}
],
"source": [
"ds = load_multiple_streaming_datasets(dataset_names, dataset_config_names=dataset_config_names, text_column_names=text_column_names, use_auth_token=True)\n",
"\n"
]
},
{
"cell_type": "markdown",
"id": "2d63b2d2-f68a-4d74-b7f1-5127f6d16605",
"metadata": {
"id": "2d63b2d2-f68a-4d74-b7f1-5127f6d16605"
},
"source": [
"## Prepare Processor and Pre-Process Data"
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "imRHJOpm4V_j",
"metadata": {
"id": "imRHJOpm4V_j"
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"Found cached dataset common_voice_11_0 (/home/ubuntu/.cache/huggingface/datasets/mozilla-foundation___common_voice_11_0/el/11.0.0/f8e47235d9b4e68fa24ed71d63266a02018ccf7194b2a8c9c598a5f3ab304d9f)\n",
"Found cached dataset fleurs (/home/ubuntu/.cache/huggingface/datasets/google___fleurs/el_gr/2.0.0/aabb39fb29739c495517ac904e2886819b6e344702f0a5b5283cb178b087c94a)\n",
"Found cached dataset common_voice_11_0 (/home/ubuntu/.cache/huggingface/datasets/mozilla-foundation___common_voice_11_0/el/11.0.0/f8e47235d9b4e68fa24ed71d63266a02018ccf7194b2a8c9c598a5f3ab304d9f)\n"
]
}
],
"source": [
"from datasets import IterableDatasetDict\n",
"raw_datasets = IterableDatasetDict()\n",
"\n",
"raw_datasets[\"train\"] = load_multiple_streaming_datasets(dataset_names, dataset_config_names=dataset_config_names, text_column_names=text_column_names, use_auth_token=True)\n",
"raw_datasets[\"test\"] = load_dataset(\"mozilla-foundation/common_voice_11_0\", \"el\", split=\"test\", streaming=False, use_auth_token=True)\n",
"\n",
"\n",
"#raw_datasets = raw_datasets.remove_columns([\"accent\", \"age\", \"client_id\", \"down_votes\", \"gender\", \"locale\", \"path\", \"segment\", \"up_votes\"])\n",
"\n",
"#raw_datasets[\"train\"] = load_multiple_streaming_datasets(dataset_names, \"el\", split=\"\", use_auth_token=True)\n",
"#raw_datasets[\"test\"] = load_multiple_streaming_datasets(dataset_names, \"el\", split=\"\", use_auth_token=True)\n",
"\n",
"# dataset_config_names = [\"el\", \"el_gr\"]\n",
"\n",
"#raw_datasets[\"train\"] = load_multiple_streaming_datasets(dataset_names, \"el\", use_auth_token=True)\n",
"#raw_datasets[\"train\"] = load_multiple_streaming_datasets(dataset_names, \"el\", splits=[\"train\", \"train\"], use_auth_token=True)\n",
"\n"
]
},
{
"cell_type": "markdown",
"id": "601c3099-1026-439e-93e2-5635b3ba5a73",
"metadata": {
"id": "601c3099-1026-439e-93e2-5635b3ba5a73"
},
"source": [
"The ASR pipeline can be de-composed into three stages: \n",
"1) A feature extractor which pre-processes the raw audio-inputs\n",
"2) The model which performs the sequence-to-sequence mapping \n",
"3) A tokenizer which post-processes the model outputs to text format\n",
"\n",
"In đ¤ Transformers, the Whisper model has an associated feature extractor and tokenizer, \n",
"called [WhisperFeatureExtractor](https://huggingface.co/docs/transformers/main/model_doc/whisper#transformers.WhisperFeatureExtractor)\n",
"and [WhisperTokenizer](https://huggingface.co/docs/transformers/main/model_doc/whisper#transformers.WhisperTokenizer) \n",
"respectively. To make our lives simple, these two objects are wrapped under a single class, called the [WhisperProcessor](https://huggingface.co/docs/transformers/model_doc/whisper#transformers.WhisperProcessor). We can call the WhisperProcessor to perform \n",
"both the audio pre-processing and the text token post-processing. In doing so, we only need to keep track of two objects during training: \n",
"the `processor` and the `model`.\n",
"\n",
"If using a multilingual checkpoint, you should set the `\"language\"` to your target text language. You should also set the task to `\"transcribe\"` for speech recogntition and `\"translate\"` for speech translation. These arguments modify the behaviour of the tokenizer - they should be set correctly to ensure the target labels are encoded properly. These arguments should be omitted for English-only fine-tuning."
]
},
{
"cell_type": "code",
"execution_count": 11,
"id": "77d9f0c5-8607-4642-a8ac-c3ab2e223ea6",
"metadata": {
"id": "77d9f0c5-8607-4642-a8ac-c3ab2e223ea6"
},
"outputs": [],
"source": [
"from transformers import WhisperProcessor\n",
"\n",
"processor = WhisperProcessor.from_pretrained(\"emilios/whisper-medium-el\", language=\"Greek\", task=\"transcribe\")\n",
"#processor = WhisperProcessor.from_pretrained(\"emilios/whisper-medium-el\", language=\"Greek\", task=\"transcribe\", load_in_8bit=True)\n",
"#processor = WhisperProcessor.from_pretrained(\"farsipal/whisper-small-el\", language=\"Greek\", task=\"transcribe\")\n"
]
},
{
"cell_type": "markdown",
"id": "381acd09-0b0f-4d04-9eb3-f028ac0e5f2c",
"metadata": {
"id": "381acd09-0b0f-4d04-9eb3-f028ac0e5f2c"
},
"source": [
"### Pre-Process Data"
]
},
{
"cell_type": "markdown",
"id": "bf10cd3e-924e-44fc-8790-46e413de7b3d",
"metadata": {
"id": "bf10cd3e-924e-44fc-8790-46e413de7b3d"
},
"source": [
"Let's have a look at the dataset features. Pay particular attention to the `\"audio\"` column - this details the sampling rate of our audio inputs:"
]
},
{
"cell_type": "code",
"execution_count": 12,
"id": "ab5a13b4-9bd4-4aa0-aef2-b3de9b762988",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "ab5a13b4-9bd4-4aa0-aef2-b3de9b762988",
"outputId": "10050f16-519c-4211-9e80-0f4928a3559d"
},
"outputs": [
{
"data": {
"text/plain": [
"{'audio': Audio(sampling_rate=16000, mono=True, decode=True, id=None),\n",
" 'sentence': Value(dtype='string', id=None)}"
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"raw_datasets[\"train\"].features"
]
},
{
"cell_type": "markdown",
"id": "5a679f05-063d-41b3-9b58-4fc9c6ccf4fd",
"metadata": {
"id": "5a679f05-063d-41b3-9b58-4fc9c6ccf4fd"
},
"source": [
"Since our input audio is sampled at 48kHz, we need to _downsample_ it to\n",
"16kHz prior to passing it to the Whisper feature extractor, 16kHz being the sampling rate expected by the Whisper model. \n",
"\n",
"We'll set the audio inputs to the correct sampling rate using dataset's \n",
"[`cast_column`](https://huggingface.co/docs/datasets/package_reference/main_classes.html?highlight=cast_column#datasets.DatasetDict.cast_column)\n",
"method. This operation does not change the audio in-place, \n",
"but rather signals to `datasets` to resample audio samples _on the fly_ the \n",
"first time that they are loaded:"
]
},
{
"cell_type": "code",
"execution_count": 13,
"id": "3ab6a724-3d1e-478b-a9e9-d2f85feb6c39",
"metadata": {
"id": "3ab6a724-3d1e-478b-a9e9-d2f85feb6c39"
},
"outputs": [],
"source": [
"from datasets import Audio\n",
"\n",
"raw_datasets = raw_datasets.cast_column(\"audio\", Audio(sampling_rate=16000))"
]
},
{
"cell_type": "markdown",
"id": "161322c2-94f3-4d26-9e1d-d9d5202ca3cf",
"metadata": {
"id": "161322c2-94f3-4d26-9e1d-d9d5202ca3cf"
},
"source": [
"We'll define our pre-processing strategy. We advise that you **do not** lower-case the transcriptions or remove punctuation unless mixing different datasets. This will enable you to fine-tune Whisper models that can predict punctuation and casing. Later, you will see how we can evaluate the predictions without punctuation or casing, so that the models benefit from the WER improvement obtained by normalising the transcriptions while still predicting fully formatted transcriptions."
]
},
{
"cell_type": "code",
"execution_count": 14,
"id": "d041650e-1c48-4439-87b3-5b6f4a514107",
"metadata": {
"id": "d041650e-1c48-4439-87b3-5b6f4a514107"
},
"outputs": [],
"source": [
"import string\n",
"import re\n",
"\n",
"do_lower_case = True\n",
"do_remove_punctuation = False\n",
"\n",
"#normalizer = BasicTextNormalizer()\n",
"\n",
"punctuation_to_remove = string.punctuation.replace(\"'\", \"\") # don't remove apostrophes\n",
"punctuation_to_remove_regex = f\"[{''.join(punctuation_to_remove)}]\"\n",
"\n",
"if do_remove_punctuation:\n",
" print(\"Removing punctuation: \", punctuation_to_remove)"
]
},
{
"cell_type": "markdown",
"id": "bfaa935b-a11d-497c-88c1-0c4d1bb3247b",
"metadata": {
"id": "bfaa935b-a11d-497c-88c1-0c4d1bb3247b"
},
"source": [
"Now we can write a function to prepare our data ready for the model:\n",
"1. We load and resample the audio data by calling `batch[\"audio\"]`. As explained above, đ¤ Datasets performs any necessary resampling operations on the fly.\n",
"2. We use the feature extractor to compute the log-Mel spectrogram input features from our 1-dimensional audio array.\n",
"3. We perform any optional pre-processing (lower-case or remove punctuation).\n",
"4. We encode the transcriptions to label ids through the use of the tokenizer."
]
},
{
"cell_type": "code",
"execution_count": 15,
"id": "c085911c-a10a-41ef-8874-306e0503e9bb",
"metadata": {
"id": "c085911c-a10a-41ef-8874-306e0503e9bb"
},
"outputs": [],
"source": [
"def prepare_dataset(batch):\n",
" # load and (possibly) resample audio datato 16kHz\n",
" audio = batch[\"audio\"]\n",
"\n",
" # compute log-Mel input features from input audio array \n",
" batch[\"input_features\"] = processor.feature_extractor(audio[\"array\"], sampling_rate=audio[\"sampling_rate\"]).input_features[0]\n",
" # compute input length of audio sample in seconds\n",
" batch[\"input_length\"] = len(audio[\"array\"]) / audio[\"sampling_rate\"]\n",
" \n",
" # optional pre-processing steps\n",
" transcription = batch[\"sentence\"]\n",
" #transcription = batch[\"transcription\"]\n",
" if do_lower_case:\n",
" transcription = transcription.lower()\n",
" if do_remove_punctuation:\n",
" transcription = re.sub(punctuation_to_remove_regex, \" \", transcription).strip()\n",
" \n",
" # encode target text to label ids\n",
" batch[\"labels\"] = processor.tokenizer(transcription).input_ids\n",
" return batch"
]
},
{
"cell_type": "markdown",
"id": "70b319fb-2439-4ef6-a70d-a47bf41c4a13",
"metadata": {
"id": "70b319fb-2439-4ef6-a70d-a47bf41c4a13"
},
"source": [
"We can apply the data preparation function to all of our training examples using đ¤ Datasets' `.map` method. We'll remove all of the columns from the raw training data, leaving just the `input_features` and `labels` defined in the `prepare_dataset` function:"
]
},
{
"cell_type": "code",
"execution_count": 16,
"id": "a37a7cdb-9013-427f-8de9-6a8d0e9dc684",
"metadata": {
"id": "a37a7cdb-9013-427f-8de9-6a8d0e9dc684"
},
"outputs": [
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "1d964121a24b4f4dbd3ce7b21112b05c",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
" 0%| | 0/6430 [00:00 Dict[str, torch.Tensor]:\n",
" # split inputs and labels since they have to be of different lengths and need different padding methods\n",
" # first treat the audio inputs by simply returning torch tensors\n",
" input_features = [{\"input_features\": feature[\"input_features\"]} for feature in features]\n",
" batch = self.processor.feature_extractor.pad(input_features, return_tensors=\"pt\")\n",
"\n",
" # get the tokenized label sequences\n",
" label_features = [{\"input_ids\": feature[\"labels\"]} for feature in features]\n",
" # pad the labels to max length\n",
" labels_batch = self.processor.tokenizer.pad(label_features, return_tensors=\"pt\")\n",
"\n",
" # replace padding with -100 to ignore loss correctly\n",
" labels = labels_batch[\"input_ids\"].masked_fill(labels_batch.attention_mask.ne(1), -100)\n",
"\n",
" # if bos token is appended in previous tokenization step,\n",
" # cut bos token here as it's append later anyways\n",
" if (labels[:, 0] == self.processor.tokenizer.bos_token_id).all().cpu().item():\n",
" labels = labels[:, 1:]\n",
"\n",
" batch[\"labels\"] = labels\n",
"\n",
" return batch"
]
},
{
"cell_type": "markdown",
"id": "3cae7dbf-8a50-456e-a3a8-7fd005390f86",
"metadata": {
"id": "3cae7dbf-8a50-456e-a3a8-7fd005390f86"
},
"source": [
"Let's initialise the data collator we've just defined:"
]
},
{
"cell_type": "code",
"execution_count": 21,
"id": "fc834702-c0d3-4a96-b101-7b87be32bf42",
"metadata": {
"id": "fc834702-c0d3-4a96-b101-7b87be32bf42"
},
"outputs": [],
"source": [
"data_collator = DataCollatorSpeechSeq2SeqWithPadding(processor=processor)"
]
},
{
"cell_type": "markdown",
"id": "d62bb2ab-750a-45e7-82e9-61d6f4805698",
"metadata": {
"id": "d62bb2ab-750a-45e7-82e9-61d6f4805698"
},
"source": [
"### Evaluation Metrics"
]
},
{
"cell_type": "markdown",
"id": "66fee1a7-a44c-461e-b047-c3917221572e",
"metadata": {
"id": "66fee1a7-a44c-461e-b047-c3917221572e"
},
"source": [
"We'll use the word error rate (WER) metric, the 'de-facto' metric for assessing \n",
"ASR systems. For more information, refer to the WER [docs](https://huggingface.co/metrics/wer). We'll load the WER metric from đ¤ Evaluate:"
]
},
{
"cell_type": "code",
"execution_count": 22,
"id": "b22b4011-f31f-4b57-b684-c52332f92890",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 49,
"referenced_widgets": [
"763a13d8684c477da8fe6f3bc5d6f8a0",
"af18d0ee0270420f98b40effce8c00c3",
"e09543b4a2cc487a97c3e4388481784f",
"fa0f9ecbfc9d4facacd3fb0a000904f2",
"70204cb91a0c4a4cbd24a56933f4aa72",
"a693eb68b48a49f9b3a44f2fb741d024",
"fbbf0b2e108747b4a19a3101e83e96cf",
"ac6dc9da692c47afbd94f2d7900f4fa8",
"630e2d7f275e4c4890ff1616c0451621",
"7faee8a8d650406d93ffefe8613ee42d",
"bde3af431a5144ba84225fd6bad9b27a"
]
},
"id": "b22b4011-f31f-4b57-b684-c52332f92890",
"outputId": "82a1180e-1d02-4a0c-ecc7-899f445312c0"
},
"outputs": [],
"source": [
"import evaluate\n",
"\n",
"metric = evaluate.load(\"wer\")"
]
},
{
"cell_type": "markdown",
"id": "509f96d7-3f11-4f37-add9-f74a0c44f3fc",
"metadata": {
"id": "509f96d7-3f11-4f37-add9-f74a0c44f3fc"
},
"source": [
"We then simply have to define a function that takes our model \n",
"predictions and returns the WER metric. This function, called\n",
"`compute_metrics`, first replaces `-100` with the `pad_token_id`\n",
"in the `label_ids` (undoing the step we applied in the \n",
"data collator to ignore padded tokens correctly in the loss).\n",
"It then decodes the predicted and label ids to strings. Finally,\n",
"it computes the WER between the predictions and reference labels. \n",
"Here, we have the option of evaluating with the 'normalised' transcriptions \n",
"and predictions. We recommend you set this to `True` to benefit from the WER \n",
"improvement obtained by normalising the transcriptions."
]
},
{
"cell_type": "code",
"execution_count": 23,
"id": "a11d1bfc-9e28-460f-a287-72d8f7bc1acb",
"metadata": {
"id": "a11d1bfc-9e28-460f-a287-72d8f7bc1acb"
},
"outputs": [],
"source": [
"#Â evaluate with the 'normalised' WER\n",
"do_normalize_eval = True\n",
"\n",
"def compute_metrics(pred):\n",
" pred_ids = pred.predictions\n",
" label_ids = pred.label_ids\n",
"\n",
" # replace -100 with the pad_token_id\n",
" label_ids[label_ids == -100] = processor.tokenizer.pad_token_id\n",
"\n",
" # we do not want to group tokens when computing the metrics\n",
" pred_str = processor.tokenizer.batch_decode(pred_ids, skip_special_tokens=True, normalize=do_normalize_eval)\n",
" label_str = processor.tokenizer.batch_decode(label_ids, skip_special_tokens=True, normalize=do_normalize_eval)\n",
"\n",
" wer = 100 * metric.compute(predictions=pred_str, references=label_str)\n",
"\n",
" return {\"wer\": wer}"
]
},
{
"cell_type": "markdown",
"id": "daf2a825-6d9f-4a23-b145-c37c0039075b",
"metadata": {
"id": "daf2a825-6d9f-4a23-b145-c37c0039075b"
},
"source": [
"###Â Load a Pre-Trained Checkpoint"
]
},
{
"cell_type": "markdown",
"id": "437a97fa-4864-476b-8abc-f28b8166cfa5",
"metadata": {
"id": "437a97fa-4864-476b-8abc-f28b8166cfa5"
},
"source": [
"Now let's load the pre-trained Whisper `small` checkpoint. Again, this \n",
"is trivial through use of đ¤ Transformers!"
]
},
{
"cell_type": "code",
"execution_count": 24,
"id": "5a10cc4b-07ec-4ebd-ac1d-7c601023594f",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 81,
"referenced_widgets": [
"f5e0f88d26b945bea293b9e395ba225a",
"781a7cbecd2d4f5682785084bfbded85",
"849af3c95ca84b03985fb5613a7c9585",
"b81d7f526ee74297a80e8fe33d2106b0",
"3ed5de0ab0f846d69ac3fd17b783371e",
"4f7e1454bfcb4d74bb05a556a13071d8",
"23c4f25ebdc54c2daa36cded24c02dc6",
"2fb2b151ebd54ae0afc4423ebcc7a188",
"1a0e147cb34a43b188cbfdf6956dda54",
"da008045bf244c88b6e0c01af180939e",
"a58cf16ffd66453e900bb97e902df0b4",
"3b187e8d68e040dabb9e00a6f7a5e7ab",
"bbf85e4741394c548136e1dc1060f03f",
"007a9bff95c64a3689f1162efc8bdb65",
"364adfd4a24f43f2b7c65c21928b4d1d",
"d34d5eaf6bea44bbb5e9832c3d2b4c32",
"0a9b7eccba9a47cca67ec37eb1b79c1b",
"30a74dda6a7f4b2e8e3d508f27680a1e",
"7c3248075c0840b1a3e9f0afa9f46824",
"67b5c4edf64d443ba53f6f4fbde22880",
"7a39271725614a07a7f8e72bab6f0e51",
"41b629d254014220bc76a60ffdc62b44"
]
},
"id": "5a10cc4b-07ec-4ebd-ac1d-7c601023594f",
"outputId": "b6c255be-8f5e-4045-b9e0-09b8196263d1"
},
"outputs": [],
"source": [
"from transformers import WhisperForConditionalGeneration\n",
"\n",
"model = WhisperForConditionalGeneration.from_pretrained(\"emilios/whisper-medium-el\" )\n",
"#model = WhisperForConditionalGeneration.from_pretrained(\"emilios/whisper-medium-el\", device_map='auto', load_in_8bit=True)\n",
"#model = WhisperForConditionalGeneration.from_pretrained(\"farsipal/whisper-small-el\")\n",
"\n",
"#model=torch.compile(model0)"
]
},
{
"cell_type": "markdown",
"id": "a15ead5f-2277-4a39-937b-585c2497b2df",
"metadata": {
"id": "a15ead5f-2277-4a39-937b-585c2497b2df"
},
"source": [
"Override generation arguments - no tokens are forced as decoder outputs (see [`forced_decoder_ids`](https://huggingface.co/docs/transformers/main_classes/text_generation#transformers.generation_utils.GenerationMixin.generate.forced_decoder_ids)), no tokens are suppressed during generation (see [`suppress_tokens`](https://huggingface.co/docs/transformers/main_classes/text_generation#transformers.generation_utils.GenerationMixin.generate.suppress_tokens)). Set `use_cache` to False since we're using gradient checkpointing, and the two are incompatible:"
]
},
{
"cell_type": "code",
"execution_count": 25,
"id": "62038ba3-88ed-4fce-84db-338f50dcd04f",
"metadata": {
"id": "62038ba3-88ed-4fce-84db-338f50dcd04f"
},
"outputs": [],
"source": [
"model.config.forced_decoder_ids = None\n",
"model.config.suppress_tokens = []\n",
"model.config.use_cache = False\n",
"\n",
"model.config.dropout = 0.05\n",
"model.config.attention_dropout = 0.05"
]
},
{
"cell_type": "markdown",
"id": "2178dea4-80ca-47b6-b6ea-ba1915c90c06",
"metadata": {
"id": "2178dea4-80ca-47b6-b6ea-ba1915c90c06"
},
"source": [
"### Define the Training Configuration"
]
},
{
"cell_type": "markdown",
"id": "c21af1e9-0188-4134-ac82-defc7bdcc436",
"metadata": {
"id": "c21af1e9-0188-4134-ac82-defc7bdcc436"
},
"source": [
"In the final step, we define all the parameters related to training. Here, you can set the `max_steps` to train for longer. For more detail on the training arguments, refer to the Seq2SeqTrainingArguments [docs](https://huggingface.co/docs/transformers/main_classes/trainer#transformers.Seq2SeqTrainingArguments)."
]
},
{
"cell_type": "code",
"execution_count": 26,
"id": "0ae3e9af-97b7-4aa0-ae85-20b23b5bcb3a",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "0ae3e9af-97b7-4aa0-ae85-20b23b5bcb3a",
"outputId": "7290f729-fb46-4190-dcc5-5cf01e1c9808"
},
"outputs": [],
"source": [
"from transformers import Seq2SeqTrainingArguments\n",
"\n",
"training_args = Seq2SeqTrainingArguments(\n",
" output_dir=\"./whisper-medium-el\", # your repo name\n",
" #output_dir=\"./whisper-small-el\", # your repo name\n",
" per_device_train_batch_size=32,\n",
" #gradient_accumulation_steps=1, # increase by 2x for every 2x decrease in batch size\n",
" learning_rate=1e-5,\n",
" warmup_steps=500,\n",
" max_steps=7000,\n",
" ignore_data_skip = True,\n",
" #resume_from_checkpoint=\"checkpoint-4000\",\n",
" gradient_checkpointing=True,\n",
" fp16=True,\n",
" evaluation_strategy=\"steps\",\n",
" per_device_eval_batch_size=16,\n",
" predict_with_generate=True,\n",
" generation_max_length=225,\n",
" save_steps=1000,\n",
" eval_steps=1000,\n",
" logging_steps=25,\n",
" report_to=[\"tensorboard\"],\n",
" load_best_model_at_end=True,\n",
" metric_for_best_model=\"wer\",\n",
" greater_is_better=False,\n",
" push_to_hub=True,\n",
" #optim=\"adamw_bnb_8bit\"\n",
")\n"
]
},
{
"cell_type": "code",
"execution_count": 27,
"id": "o72eOpGzD_sK",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "o72eOpGzD_sK",
"outputId": "f26c4279-5dc0-4daa-ffde-b53e8ddd237b"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Wed Dec 14 10:24:09 2022 \n",
"+-----------------------------------------------------------------------------+\n",
"| NVIDIA-SMI 515.65.01 Driver Version: 515.65.01 CUDA Version: 11.7 |\n",
"|-------------------------------+----------------------+----------------------+\n",
"| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |\n",
"| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |\n",
"| | | MIG M. |\n",
"|===============================+======================+======================|\n",
"| 0 NVIDIA A100-SXM... On | 00000000:06:00.0 Off | 0 |\n",
"| N/A 31C P0 46W / 400W | 2MiB / 40960MiB | 0% Default |\n",
"| | | Disabled |\n",
"+-------------------------------+----------------------+----------------------+\n",
" \n",
"+-----------------------------------------------------------------------------+\n",
"| Processes: |\n",
"| GPU GI CI PID Type Process name GPU Memory |\n",
"| ID ID Usage |\n",
"|=============================================================================|\n",
"| No running processes found |\n",
"+-----------------------------------------------------------------------------+\n"
]
}
],
"source": [
"!nvidia-smi"
]
},
{
"cell_type": "markdown",
"id": "b3a944d8-3112-4552-82a0-be25988b3857",
"metadata": {
"id": "b3a944d8-3112-4552-82a0-be25988b3857"
},
"source": [
"**Note**: if one does not want to upload the model checkpoints to the Hub, \n",
"set `push_to_hub=False`."
]
},
{
"cell_type": "markdown",
"id": "393c883e-3e50-492c-bd58-f51dbf15ee56",
"metadata": {
"id": "393c883e-3e50-492c-bd58-f51dbf15ee56"
},
"source": [
"We then define a custom [Callback](https://huggingface.co/docs/transformers/main_classes/callback) that is called by the đ¤ Trainer on the end of each epoch. The Callback reinitialises and reshuffles the streaming dataset at the beginning of each new epoch - this gives different shuffling across our subsets for every epoch."
]
},
{
"cell_type": "code",
"execution_count": 28,
"id": "3ac16b62-b3c0-4c68-8f3d-9ecf471534b2",
"metadata": {
"id": "3ac16b62-b3c0-4c68-8f3d-9ecf471534b2"
},
"outputs": [],
"source": [
"from transformers import TrainerCallback\n",
"from transformers.trainer_pt_utils import IterableDatasetShard\n",
"from torch.utils.data import IterableDataset\n",
"\n",
"# trainer callback to reinitialise and reshuffle the streamable datasets at the beginning of each epoch\n",
"class ShuffleCallback(TrainerCallback):\n",
" def on_epoch_begin(self, args, state, control, train_dataloader, **kwargs):\n",
" if isinstance(train_dataloader.dataset, IterableDatasetShard):\n",
" pass # set_epoch() is handled by the Trainer\n",
" elif isinstance(train_dataloader.dataset, IterableDataset):\n",
" train_dataloader.dataset.set_epoch(train_dataloader.dataset._epoch + 1)"
]
},
{
"cell_type": "markdown",
"id": "bac29114-d226-4f54-97cf-8718c9f94e1e",
"metadata": {
"id": "bac29114-d226-4f54-97cf-8718c9f94e1e"
},
"source": [
"We can forward the training arguments to the đ¤ Trainer along with our model,\n",
"dataset, data collator, `compute_metrics` function and custom callback:"
]
},
{
"cell_type": "code",
"execution_count": 29,
"id": "d546d7fe-0543-479a-b708-2ebabec19493",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 1000,
"referenced_widgets": [
"880abc8c37b24cb5991a1f54dd48e903",
"5c30643d2d254d16998ff53a6b28f2f0",
"d535dcb265264004a40726c31141517d",
"b5e159b1582846bbb94d68615af41515",
"6a10a26765464e8f81da824dfbbd77a1",
"4f127db3fc4d4505afefc168ac621637",
"4651dea7cc9440bdaec2675b4766139c",
"b669080822fc40a2bd6a5e340fd7929c",
"febd8c544c604178bf5ff5c315b61503",
"8ccd19f6fb3f4158b644a9410f70bc39",
"bd4825bf7a04400798e801de43b60608",
"eb007223e1654d258d6f3843f574c899",
"c51c7d0f0dec414683b70090df588019",
"dd6721488d6848e79944223d25a8b984",
"2210d63c94f04880aa505e53349b811b",
"76093ca102ed4eb597c67c31d35ea4ca",
"481806eefb42436b867939f85cef2af3",
"ce40a715dd864732a1d44a9a7345ea8f",
"dfdcf3403fad4a5c8e0ad6abaaf710c4",
"8c23acef1a1944d7b858507a76a241af",
"c5346e5d44a64584999b2e5471062470",
"dd78c7bb11fc4bc0b0dcd66ef957352a",
"2752decf62464ed19611abb011700c94",
"001435de01d34a339c3950dca389520d",
"daf9d7c783d249a1b61f5f9a50a3afd7",
"bdac5419bfc34ba991d5f87607e88f23",
"5b8df662a09a4f52bef83d59696f2357",
"cf5682dbf09c48c0bdf9e2ed3bf7b4e3",
"80ad52e758584edf9c63aeb23c110faa",
"c35c7b46ca594b69949f8a7699a4c3eb",
"992a789195e944b7865d426e8825b6f8",
"b25d89d861c64f8faa4e3ae1333a828c",
"a4d3485b96564b7bb626fdcbe8e6c79d",
"e71553d5af9e452b8764ad0ded827b49",
"bfcb8f1a4df04aa5a0637eef0a2d3883",
"ac6a32341a33402fa03c80a944499657",
"43f8afc7f14042e6abb21cdda885bb60",
"c80005e8917940309ffd431f002bd17f",
"063b61cf67004b37944a87a245c8e22a",
"4950ae9f87234544bdbe3c0ebb2cdab7",
"dcaafa43f94b4610bda583f07cfed68b",
"4b2977855b88426cbbb1ee1ce7b75c42",
"434eeaa10bbf45b4899f13d6016bc0e3",
"9374611e36ee4bacba6ec4d1d3660a3a",
"5242d4bf835740a8a756a1a979bd3e71",
"e1737cfceb154cd39cd7db68ca7de4be",
"4b8ad2778a7a486f803c1414cedc8690",
"a44bb95a207c42c687aac67625ce5f40",
"df05bddae73945ccbedc4611b4157782",
"904291592fec4cdb960d4a2c6e953a09",
"5713838af6624aa6b8db26d53c425144",
"138eb8b7a5d14857a16216ef1427c551",
"dbc89c6b2fd140a1a5dc579c10c85e4c",
"14b6c40f80a34d39a2f81a43e9898ab6",
"356409f4a0ac498589c8abf6564f0aa9",
"02947d5ab8af45b2b561cd912a91397b",
"ee36bcc132cb403bb31427a9162efda7",
"ef72df01007d4538aac41b5c283d40de",
"595f2c343eb74c909c46ef89d1723e61",
"bcb6f7ac5a534bfba2d2bb632de09f93",
"0bbdb81f01184e68a0972fe807be7738",
"8c97444c4fdf48158a91560a505d0c60",
"3839ff27494e4b6b895efebcc5cdf749",
"02da1cff196345e08466a318dd0bbcff",
"c84c44be802541db8f5836f28ee2b77c",
"611d279a6cdd495ba32149bb6f93e3aa",
"0ba5b19da6c84872a72e815b6193bb5f",
"9d322c207edb44d198604acb75d99120",
"7ae857f34e77426e84090efeb8504782",
"aa0d0ad41bfd4266af7e017a2300a7fe",
"75ee3cfe47164826bc124e92f5f39c5f",
"0f1711f2dd254bbbac614fab33881fac",
"9137b795af484644a1da3d0cdfc798a7",
"576816de6e2c4505913eed89e344d7c3",
"83663781210a47c3a4e9020b18bae5ef",
"0dda93450a8f40a2b5fcacd3edefdf81",
"70cbc90488d441c6b5403ebd43559662",
"41f741e142a0458cad14e33388227224",
"57c81067f6f44d8c9521210403cf5a23",
"69baf6fe01fa44a594a2cadbce091f1a",
"4faf17924efa4b278740ccf38e88537a",
"f824b503aded44e199aacb265e1b505e",
"bed1f18e78a94222971545247aafe20d",
"b33ae34ac62949a7a6324ee551a0af98",
"e8a60ab53a68497a88804486aa49453e",
"bfd93fbf8d7b4055b554e257e1164454",
"a5b5252e9bcc4d2eaa3566c41ff68e9e",
"7f55c4f55ec94e528f8942da1f0dee4e",
"797b5246a72d491897922aa19bbecb50",
"523bd0fa897b4588a94b3d6f0c7fc74d",
"ccf8b65d2e96459f8bd1c85027a8ff56",
"4f13b62b337c4b3e87dc999451d2eba3",
"36f255d22a5341beb926dd137d9b6dbd",
"77c864de12644ef292c8160e56d97106",
"7b1504666e9b4e149c176f4aa8f4f1c2",
"88e9208b3481463585e8482637fab334",
"b40a29a1a8414653960109031148136f",
"f555aa8a6621467da08e63b7b4254696",
"3e5c046b21664d018cd11665735ab1c9",
"4f5182f970cf4ca3ae997a9a2da91130",
"6214a82db4644693b36d5384fc1a8099",
"79e2aa3dcdb247c4bfeeca1e71000f49",
"1b62af075d8b46f5a8acbe1087598f13",
"53af5e5e50824d65bd0f4f6883cd370b",
"b97e2b53719c4fa58357e6b656e0ea19",
"a48324d6fa5b429e973a5cefc9329421",
"bd551fda69cd4159ad11e73512562b4d",
"0f5f5674d9bb48b7b248a1f8c5e8f5bb",
"3be82e9f3c794cd78e94740205e513c5",
"8052181f253e4aa8840a3db3b3690855",
"9a3fd8ebfa9b46bda6cc0e4a8bdd099d",
"68f8d9cdc3a4477886be6d2bf143ba2c",
"7996b292275f420d93a5412fbdeb19d7",
"fc8db19da9a945e9abe4347e7e9f21fc",
"f0f087adbdb947fb9b35e69959fb3e13",
"d94849186ee143d08a4369e50840e3eb",
"8219a133da664afa8b264bb0a8f2d568",
"8bce0765db7a46b3bc7213105a1a64e9",
"06763f89b5544e14851056fba43946ca",
"63e9363b8d8d45aca93c0d059c693d11",
"df9305cb70a0487fbaa4cf6c8152d620",
"3d1bb2f9687f48609fb2ef37e56509fa",
"e242605137794e5ebcd46617fa0af652",
"6ec99a85a9ea4b9a84f518a21f982ce2",
"36402e96fdf440b7b5d6b16b6c6c4f92",
"7ac0c2ac640b4a129e3e46a8ccf9f504",
"69954d497f9f425d813c53e8589c573f",
"76775687316c434fa247fdc4bbcc2be6",
"af6e525f26ff407b833ae16148b24301",
"fda4893c706042f9914f1245a537e29d",
"a071ff14cbad4c0e8ff11573415ae815",
"46989affee504d00acb812ba0a69758d",
"96628a677b5d4ba984893fff79e7fef4",
"e1da82f76b8047b3b0b7ea7c2345c717",
"b360673d35ea45c1b339aa4c3409fe0c",
"4188ffe910d74d24bfdfd3674991e374",
"9ff78343c5a94d4aa3607468cb8b9e4e",
"a98bb1a6889c461c919665cc0ba959cc",
"58e89118fca14eb798aff9a5f52eb116",
"e237077521da49949a978909fe96c72c",
"b8d0caa96012455ebb27315be0ed26f0",
"d09a4754a30b4cfaa6efa49f38fcda92",
"ffc0b7aeef2d4831bc60a258e39ee53f",
"ae9501d3bc7146d596373eb35375fd21",
"9817f72e188749f3baeee633b356ed92",
"91d63d7fcb9a4a09a68af81126a82e2c",
"fed56b2edb4f4d90b866e3fb0ded3014",
"751c730379fd4931a50e2476982e07f2",
"95efa379c1be4b5bbc836d28d94970d2",
"2b15752c957a4624a8dfa7a3a9ebbe70",
"7baf43aa582945629ad3916e506b3804",
"0898b637f8334fe491eee5836c8a9974",
"b4268f54a360472e8fa2f613011c63a6",
"f33a773d9ef746379d924260776b9878",
"0abd20b47bc24b86834020dc60d527e6",
"5265abf473834cc4a03600dbbae4cde7",
"aa0f8d0482c54b23ad5612d145e9fdcd",
"fd303b63319b4a09bce7b21e425cf870",
"746fd0c20d82434ab99faa45445208be",
"a1b95dec041c4dfea4c9757ca5a00894",
"597fcb9b7ab04d0fac55f3b4504db407",
"730f066045c44fdea546e2b3356850e8",
"476029b6d01f4cc38cf072fab648dac9",
"5d19e13906e44d19ad981bc4f5ae762f",
"c3018697619a406ea680dc18626e2cc4",
"bae730bb307147cb833135d97ebb9e6b",
"47a6d0ece87c469199ccbf475cc4dbae",
"1f0740e993014efda0e421d0d7519241",
"799a1af2b69e4e5982b5ff0b8827958c",
"6469b48296b64cbf8606e3ae05bbb28f",
"0daee910afee4a2ab5e7e0e0825a73f6",
"8ec59c777fde42f6b6c7c1adabcd70ce",
"a953cb143292418993e7122a6c0e5823",
"21ca425d3d76446fa0c299ae345aa674",
"7d42b690d22a42ca8877f59012322a8a",
"e0eb0ae77bcc4f56a242c1331371b077",
"ac93135defb84024a66798b982bc0e86",
"accb69bf7b0a4e12a494e5ff67178d5d",
"9551b8aeaa5249b4b2eb3aeffa7a78a6",
"51e3e1a158ec48a8ac2a1c0407dd7bd0",
"988c6be3d8f14cf7ac1b9c4ae6789674",
"c97f301c0549422caa7333aa332a75ba",
"05ab4393ae0849fc887e8c767468b835",
"c6a5941db89b4794b9ae2c1e3e6b0fef",
"d10fc1129c8849eab48aabcd51184759",
"cfed7d21e0a949b9a980e9737ac13df3",
"2615fd5addb64b0da29c0c4f145766da",
"8937cd6533844fcaa4796b6980489491",
"716f6e5b5fbe4d139aa574d5403591de",
"a3f968f319f54b7aab7dafb9b54ac6d6",
"ae4285f145b6481bb08f618df8c12506",
"acd094f59dc4418abf490ad32585532e",
"3d4a2c7d8d854615b54d09c60ca21875",
"2f57dd6b70944ff083e6b22281a9db29",
"6d97a1b2009848248f902afa472722aa",
"c6fac07bb41d4783b1f641949787236f",
"76c5908efa08451a8704f2d9a130ed97",
"f369c87e114448afa7c75c030cfa3ad6",
"63e4cec073d745338b88defdabcacec4",
"8baaac1d018842b99dc6da618a9b3110",
"2e7e75bfa51c4ca292c1b5b8d19d52c4",
"a3eb0a48773540eca7a339b36098e78a",
"f79667891c2b45f49bea5407a8a344c9",
"0104836d49f140d9b522e3d17a95a8f4",
"a8612b17b5fb4845bceb7bd44df15bc5",
"1e05c9674fc04b5aa636a34af88e265d",
"8e201b38a88e464c9a306e9e0a83e1ed",
"f82ca058557647b1a5d957bd01b59709",
"4d2f95ccefb34e5aaa98f9b947071852",
"ec67367413dd4631b03c943720d6c908",
"18aaf26d5f5f4d00b594fdc9d4589f02",
"9b533a2c3c1a4507b495f89c78d9a9b2",
"e002b0bec0c942ffbe043b3bcbec029c",
"2a4751915df049f8833c70168aadbce9",
"06ea5f4a63b44eb19eb61bc889f2eb78",
"cabacb3d2c654a62b03adfe4d5e5ff7e",
"8a2a9fb7d16f467ba9577a13822d1fd1",
"d09ef086337844478933bd9b2879ba3a",
"a5350a014cb24918a4f77dd2815692e6",
"4401c3e8d7fa41208ba7af1d53874940",
"3feb38f1670043eabb1f6df5797c6df5",
"2680836d97894f3b94e39dacbd12aace",
"817270b094af4b19a6d1a33dc70ed3db",
"aa152c82f23b47098c3b30d80c6125db",
"a27945ceab6343d08ecaa806340d263b",
"058ef819cc6e47319bd426672d10b020",
"85609060c11a47feaa029c8c885c0729",
"c95e3f89f1994823a5825566c57baed7",
"66891c83896842e7ac156fbb32371735",
"9e91d30c2aca48a4b34e7b7d8ae83148",
"81edcc8b90234cbf9dc8e48eec657d97",
"2de3a303af2d487ebe827da63e820eb5",
"4eb578564d1c43a19bdb46a3f74ac81b",
"fe9bacb95ec446499e18f05d74347799",
"bc5b996fefba4f30bfd4cae6047bf100",
"21a1deb481b0448cb1079ff1fb968e8d",
"cc3fa956813b41a3b5405e931dd56eaa",
"9f4b909578c94c57a67e29a16f0dc2dd",
"546d55fbc867400e9d20e70ca9a3e54a",
"3fae5ad99cdf4e399dfe97007e77d8fa",
"bbf4aac9ddd64f8b95eb74b8660d5cad",
"0486557e705347dbbba666f5e710f48f",
"b6ee6dd31e6545c7b15a0b56e9aaec0a",
"55da43ed78b4477e92947f7f6ebba3a9",
"30f88148fb5c4ab0b4baf54b63391ba0",
"a3dfac4e0bb7445083191ce2adec2d7f",
"1d3d9c0936144895b6f1340ec31121cf",
"923590bc5d5547fe85a71f2aa6d304f8",
"6f3a14ddc93b40709850daabf2a8f2e8",
"284ee1e584ba4286816e62c19554152c",
"9295b973124d491797fcd937e66cbb50",
"5c028211a13644f488e9537b6c9d8376",
"7e42bea633794c5caba5711fd34f0834",
"4874b62939814590bea4e5fc2f42c69b",
"36f2f69fbc66485b8e63bec665e76d7f",
"cd854a9dce3b472a9af7e5488bfe2c94",
"57832ba6b2cc46bbb5b2e81460a43a4a",
"3538cecbd403403d8421f1a1adddd853",
"97a1672850aa409ea54dee1b33d191b9",
"b65dfe10ff294053828fde7c6dbb9b99",
"950546eac6c04b81b4d5c016992988fc",
"9b4a1aee90474cc69d7577ef933519f5",
"f26979e2ebf844cfa8fa81a82c511f6c",
"3a0bdf5c8efe4155acffa424b00120a7",
"b4b33be47200493e9fe03ff101be5114",
"e3b98dcc3d67410b9e5f03dbc4df95d4",
"50b02ecd7c9a4af19578d1c471d6ac77",
"a8151fcdbf9e43e280926e1bc8b8dc33",
"c40b75a193624f7b87eb3b3d04246065",
"53b5923eee60447c8a98e95f320035c1",
"57ad0af620354b91bd7ad272c4855e73",
"0085ef5074984e37b730ce57ca37abae",
"47e77d50d524403fa499648a2ea1467e",
"48415c57d7d24d458c010b73adc936b8",
"87c1c71d7fc547f9837d39e56dcd30de",
"1fdac5f458554383961fde9d003a0424",
"fccbc09015e44ea7928d200485f4ef42",
"c34171a367cf43f391f54ccd7aec3145",
"13d6735ccabb4932b1f3a7e45f95d3f7",
"77b3e933c32d4a95a21c7851239ee6e0",
"3e984743c28b4c1f970d12ce979a1578",
"96225d95b6db4e07bd2b8a3a17a166d3",
"80f7a5404dec4f198bd7e270f578e6ad",
"6e02fe5edb754e8d953e4058a9c494e1",
"7c2830d1b05d4d38abd5f904d057ff92",
"128b02b070f7454b9536bdd8d7cb8c5d",
"6dd150f39a9d4463b1ae912cbdf339d5",
"1f92270e2f8a45b5a38eedfd2a18c83d",
"fb9a93aba0ce4ff3832f4fe2cd4415b6",
"49e0b545efa1428ea23620234b511096",
"0eed5c11ddda42d2998a42b8e93844c2",
"39419a7a88474f1da5733e8e9f5a3bc7",
"aef4d8148e1c47f59c95fc2cf742f575",
"6acee8944cd342e09f889634016ad796",
"f8e6290fbb964b958cf937fd2cc0ccdb",
"91c42bd5ed0945b0966c7a8ca95736b3",
"61ab5d26f1fd4beeb04b279f52b19dd3",
"b3d546ef17c24039bfd46f654bb7b39b",
"60c2909071464ecab623b9f870179b69",
"bb384e467c2e4a9c9390d67cf5ca9a82",
"f8adbdeca8524acabefb64487b25d6dc",
"6c9041bc05104262a00e39fefcf53f58",
"aad70a3814484562be4ed89e80137f1f",
"05a70b2994144b9f8117fe802ede63c4",
"5ce46ef9de4e4759b618f9b50c53c1c8",
"1c1ed8876d2b46d09656ffb21660579c",
"6f673bb7966248d3b9056aed6a41b5a7",
"30626659e6d8486e88226467f1fbecf8",
"cea213a613654ef0b3aada20ad8bbca7",
"04a6dcd46ff04c4fa0c95b5bb32fe5a7",
"38b759b737364aba98090b4b7ded1776",
"ed76c239b2e64b72b7af12243754bd68",
"22874c3862f94d30923cc7fadd3fe38d",
"7fbdde3e90a74f89afbf1dd498140199",
"db037bd70f6a435e976e66b6eaf567dc",
"109abdd715ec40fab79875eb3c845f0b",
"d7a27a0b995241a686e7d63195baa901",
"01309ccf1d70429a82979b5023bbe0d9",
"96586a3fe4af4136b6b7c1f21eb12f95",
"2ec35e48e7f942a5bc26a49f5daebec9",
"dce7e355fe354c239f97ff1c05da9096",
"d5fb639bcd354bac830ca8b59aadc6de",
"7cf3a06b99774de9b0d4784d32bf9ef3",
"aaefcf3b6cae4958bcd7a63ea39da360",
"149481da23b04709a0f9a9a1ffb08ecf",
"2ecdb20e10a64692a820fa6efae6ff0a",
"cead097d33b14083be56b646b0cc65a4",
"91aff91f24d64a52967db9ba99c31201",
"67baf5852b924c5cbfd9bc82344c2ddd",
"5bb3500ceb164ef3a00b552ef9619aff",
"c92f8991c53944deb31ef8ee24ebe52e",
"bba718acc53b441cbd09fc3706c1de44",
"c2a1be09b3894c2eb9bf0a7e789b416d",
"5e993b4a221e412ea668701ac63b61ad",
"1d9849ace8e647a2b82ecb0d449ac6b0",
"940515a1afb443fba1a5a8d85600641d",
"28e7ee736acb4e799813553496ed9ec8",
"9d602960012b4372aefe01148eb5b23e",
"eede47c868814b7ba70c33509a28657d",
"f9a24596414f4eed96e9dce8e9c06301",
"e0303c3b97f446d5ac48ea5be38b6cd7",
"9cd3b75d6c5e4d5b846a10cb5d7b782d",
"873dc23fdfb04f728b2e05085501a48a",
"e71195474e434a40967ce5bd9d889f5b",
"fcc07288376b457ea54a2aaba0a55872",
"1947a1757c724a87aff726da74058e66",
"e7d77ab029264fa88b833c9f99f59792",
"a0ee82f83adb4fbdbed9f6f55cae5c7c",
"8c57f9d79e4e4a5fabb95a9f4ac7a133",
"31e6371eeda44771a8cecb73d1869d82",
"2c0ca30b6d0849b68862ed297f45e456",
"78699730f3ac45aaa483b72ff6312f2e",
"68d17b68c11842e6ab1ea0e697c00135",
"d7a50358129840598993832a547a04d0",
"904eac74dc07473abccbb5c539f90155",
"c05e93176b7e498fb2e30c445a4fe1a6",
"4ad86c31abd04d299196054c45670fb6",
"9b2e04f870e848b5b41bd96a69c6dc60",
"c1c4a7f579a94ed19e40385db675de25",
"27f6b46706da4b73a3e682229c68e376",
"e01a5c7d875b481290c4ddb703ba9405",
"218ba600e9fc488bb3bbe81a6258c5e4",
"c1a3b3797b37492a8746e5616d22d38d",
"242fce84516e453dad6a6a102d7cb781",
"01a0cd25ded641a1a0749e17efd8dff6",
"e48b15e9785b4e8da00985487ac0aa94",
"e27143553ccf4fdb9f077979e5ce9539",
"e07314b59f454fa2959f39fc44f51e44",
"c98aa63bdb5c43dfb9602fc5a8a6b121",
"027b422ad0024d1bbc2a2372fd78e6db",
"ebf6b6e11c104a028f0c049feb5d337c",
"a2e20b9386ef4219a63881fd56262211",
"a746ab46fada4a3f94cda31d595cdd88",
"ddada419a79a46aea03f4232b224e4f9",
"4722c712373344f6b4160f5d4553b8da",
"4f924f4940c74bfa80f67eb907918beb",
"753d2801c1c746579504da47c923db73",
"5fab5f76dfa8419e8e7dd00472f1718e",
"cff05e0d2bb342c1bb70228cbc434ba8",
"a873f4df931c4067b7a1534f845f31e8",
"373e4843d84941ce814fa4f1f76bee3a",
"4f61de8c299849ad8a4d58e3c084191f",
"77f36210cca344dfaf1be732b1204646",
"a2db4e96821940be88aed09f5e698ff0",
"c830371053cb496798004641b0165058",
"44c8758d3fa845f1b4c4b1ebf41bf7d9",
"386fb623f71046a79df863560adf4c75",
"25db983da4ad4196ba6a09c09ff78822",
"1cb76cca9b0041798bed7563fc373f80",
"1e067e32e5d647dcbc6f2a9257fec99e",
"f3e141d28f9647f0a069ad3572a4efb2",
"ee0d51099a2b49ff8d0a1efee131be76",
"3ed4699371df40faae96325b6ddf354d",
"3871dd6044cb4fa6914cb3c21d0f80dc",
"51df0ef656c44be8a33a6cbac10983a5",
"6880603885a84544bf272ac3db074be1",
"e9418409595b41a4b753571593d01815",
"0633200d486447ef845f060a9e184529",
"9cf7289783e44c32b5d664652360fd44",
"a1e61d2900ff4d61bcbdfc7043e580cb",
"3dfb0a72e2ea4b78bd49ec87b4992b3c",
"a1ef67dffc254a7fb1e60310932b68a2",
"de5c5a6a4b114e748e3068941e1a22fb",
"57734e30ccaa4784ab3cddb1d09465f0",
"40d1373e3e614eb4b01fda140b9c07ac",
"373e453ee74e46aeb98d26b3d63a7725",
"dfe11d2d83fe4a6f8385498ede690c44",
"7764dcf2ba5a41aeb4a248c7f42b9e3d",
"45ba46ab47a84eb88b2c5a8bfef54c8d",
"f50bc199417f4d4784ddd300c8604e97",
"d693bb18b2a849769c1bdbb09bcf6875",
"65ce943cf2fd408e96494463837df7f4",
"b790fb62d0814699aea9798ee972c298",
"011c4b05e4414ebfaf1a3d4e86187036",
"7868b047a75f4565a9887c678fa88c50",
"4ba46096a41b4b43a06e423be152a96b",
"7c233e8aae354af1b9ebe82bea44d5dc",
"9c4aab98a3da451fad8924621c22ecd3",
"daad6e7abc4e4e1ba47faa647e1bde80",
"f823b24386334166b83c77310bd985f6",
"639ba3de18184902a913b9d334b65289",
"79882bf9a14d431db5e25b7f84334a59",
"64c6885b0b0343ec838371706f9dad2f",
"5500883d1c194d3bb7736be2fe34ab59",
"3df87d98d3f9415295644c96503473f6",
"4f8dcc153fbd469190a6aa6949866356",
"1aa0254ab8ac4f70af66ed27add0f66f",
"d859212fa8f54187b97e18a3f349cded",
"bd84b5a90f2640e794ff9d0adbb7bc6b",
"2450b049380248b498ccbfe916258252",
"f628886f29e84dbe9ad16d47d6e64188",
"9dd9dff101d648438ee830e088ac11b8",
"e61f9a0641774cd1889d4224da9b1689",
"8416b3c8123349a9ad324a9a5be4d272",
"ad52d88f5248429db5d98ebe802f197d",
"6493c6109af14ceaa463a67ca6077f1e",
"0b31da6fc8a946469ec54c1ca9b391d4",
"fa9276650b3e4b00b817ac6027e07859",
"5baae72a38d7419f92052cdb91224ab3",
"17612db85e2b411ca6e227fb0d96f622",
"a594f50c7cab4211be7430549b8f55ea",
"a87263b067b54f7980dc9c68b939a1d6",
"6a6269ce52ab4b84a15b35f9f583dae5",
"e82f1fdf5f0142d195e180cefed50284",
"896071469caa44a5bb0a6e1bb428cd2e",
"60519ccf66444978a0af3feda4ba7c97",
"24e0e5202bbf4aeea02492497f2753e8",
"f4a2f79015aa43189bd626e70649bfc5",
"eb0a253b4a81472396be7b878fc24773",
"983ad9c6862a40ceb1fda44bed1a34ac",
"7768a9cdb759403b9a64b3fd2b231762",
"a9a2d52c93b84d999b351ab9a8820a9f",
"2c3ec8fc9b0d453c8176c52b8dddd074",
"cead2c8e1b4c439cb5cbeead55b6e947",
"e62b6348a36f4a0787b0b7a78a9d0b2d",
"d0120931d5f9450fbf8b5c4605fddfc5",
"b54ab854ee8544a582a1fc1f7518a6c1",
"2ec642cf6ef741b9875f7cccf99230a1",
"d31ff8283e7d4322a6d6ea7ef871c9ae",
"36c2229d260f449c979ad61adaff7707",
"b8ca438b34004e17afa564b6f1b582bf",
"d25a38a6420a4b3a98c5075b37e18427",
"8a96c21639bd4221a9f57650a1a6ee0c",
"eb761c1538504f279eb951b3f95f17ee",
"93ce5346a55d4573a13ff7a2fc6b9c97",
"a3fdab55f32940b48d7a06f8e8d18ed8",
"07d61adf80824ce4bf9445f1cd0744e8",
"a7a89c20a3c848ccb6c5c2293340b889",
"ce64c3d52056412c92800be5850300c9",
"f402ac404594451cb96e4d2bdbbf0afe",
"bf532b355697434e92a50cebccbccfb9",
"dbe6b45eb98a4e308744ecd5fd37297f",
"f36c0b6c8d8642e89d147079c9e0bf7f",
"907204a1237d41408fbb357d66490423",
"5693a7c225b44e04a5d51a3382c59448",
"0d04712d3000439fb0ff6c6cb61816ed",
"89da05f72308428e9dfc3598516da2b9",
"c7c6e1b8a709415296def0b91db92c4e",
"51cd2a18e7d743669ebb19319447f87f",
"bfb490b23bc441f593f7f274bb01359d",
"f247a32acae84649b86b6e896b5b744a",
"f10c7216d4174495b0a4e665c5053ac9",
"53b67fb9e4cd490faf90ea9156b07b03",
"24af5044aa60404e8e3a8ebc2e7c98a8",
"4f1212c66e3e4008abfb1b6c4d0e7472",
"2c585ecf43fc45c5948c403a65842297",
"f26d3240e3f14a6fa8a494237c55409f",
"9344ce63d25a48b29edba33187c222e8",
"351cae6d48e64722aa420aeacf2626c3",
"cdea0c411cb844fc87599aa2084d7441",
"59d6cb17d43940ef9c944b06ea922039",
"12a542c831c0422291a699807ca0cd53",
"4e07625d44964857be326ecb5096ee8d",
"37c5f53daf16401988c6e8deff9a65fb",
"bb306428c7a64b16b2f0ea4aa7b3ba15",
"fd2afbfae6384f418f0d42cf28592a86",
"b1c6592fb1944b46a34e8b746052c052",
"5a3439ded16c4bf5a8f30c7b191faa86",
"adbc37dd770046379e646a1f13780efa",
"5278239f86bc4f898b02507d764ac6db",
"1e51f7e5048b464a8172f66d518abea9",
"f4b9482f806b4a10ad97e7c8c4da8746",
"0715b457c60a43b986c412ddbfaef501",
"72af63a95299413cacab8b2341be38c1",
"dc1c855723c74457bc792f87e63ec418",
"5afe68706962419e87088b23c9e7713d",
"5792b119f2e340a687b71b9fdab60d56",
"26013aa0e3e246c8b1a0be1d01f7c932",
"a87644ea34a04606bb358d12f3226b00",
"77104052cdcf40b1b17e881081156a8f",
"82391d99c378441f906dc0b9afe6ca0a",
"0f7dfe7c8f5546f2ad5b6abe41c92e0d",
"a4e2e96150204de5bb50f1a106eb459a",
"225841333b1040d687d88440b7cccd57",
"9fb0fc5b035048d8ad64a8ee08c6948f",
"6dccf5b8dace4ad984e136d3046d626a",
"edd71b65c1a84d51a2884d8ed47e6f56",
"f3006938b02e4bb1806f5565205c4e8e",
"ccee34e496ac4c1dbc15b2f361425456",
"8acbdf4e8381431d9cb84ccbf2add064",
"9ef4c8eadc82438bb090fa1f6200a79a",
"c417e218affb453b8e936ebaebf2d1d7",
"2998e836efde47b088765077ea0fa10b",
"859a7c80ad7a46b4972f2930145acd66",
"075db7c06e5b4c9ba686aed5d73bc73c",
"737039b9f94748eaaa603ba9a6cda9e0",
"d83ef30a2d904e2b953c111d829b8127",
"f587b2bc1e5347ef872c12fd85da6910",
"6f67e6a9183b444b82cd36703d564b5a",
"a1a07ec26f2448b9a88a96b7164eab4b",
"28ed16b5ef96445383137022f6ab65bd",
"1e2f41622c844711929a57c44a811c3e",
"3da83c737d09427a8f421b17464b87fe",
"a92f546e28d34f66ad2e215ecd6c47ca",
"552ef0b11bda4867a2989e6c1ab4f37d",
"0d42b72d92e849ab83a55c30475156c4",
"a6d2fda17d9e4948848ffd175d128b2c",
"97223774f78c49a18ec028ded1290426",
"9a1a1f9e2159477aa25e9d0af33b9ddc",
"131c544c0b8a4d4fbb915da6d25a11d1",
"6e31091cffbe4b84900ec88314a33015",
"c41742c414a440d4a1814e0ed76cd33b",
"dc057697d981404aad8cff93f19c3c55",
"12ff0649c9654483a40534b64dccb410",
"4716b079cb6349e7bee0a84a293fd29c",
"854340ada2bd41a28e78b7725fb103d1",
"4d3b3c14ac5f4b9f8f3f73660545ce62",
"87b05e5476724bc5b09e7f27c8136ba4",
"54ee17c8371d4151bb21dfb4c8986b00",
"f01af2da136f42c380d33d505cc6c508",
"f16d8f8375364204a54507886f7544d5",
"fe0c0fc908da497e86621d532af79660",
"f54640ac1c8241d4859109d3beb9791d",
"4e3d2f0a7072422bb166f8c7f3a77d40",
"5b333f9b3e8b41a9bdbb44649c452a6e",
"ce64d20ea15c4a44aa4bf2b25811bb11",
"e9e67f8af2cb427389d095eb7bba03a5",
"c0a52f3bed0841389ced9e2b9bea100b",
"e83514be4a134c4fbdbf512190097759",
"579f9f181409467a986e4c36e3d217a3",
"baddde64c4f549829e82656dcda5a5db"
]
},
"id": "d546d7fe-0543-479a-b708-2ebabec19493",
"outputId": "2c83cd5c-b1cc-4a3b-8d6c-57239408a297"
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/ubuntu/./whisper-medium-el is already a clone of https://huggingface.co/emilios/whisper-medium-el. Make sure you pull the latest changes with `repo.git_pull()`.\n",
"max_steps is given, it will override any value given in num_train_epochs\n",
"Using cuda_amp half precision backend\n"
]
}
],
"source": [
"from transformers import Seq2SeqTrainer\n",
"\n",
"#import torch._dynamo as dynamo\n",
"#from dynamo import optimize\n",
"\n",
"trainer = Seq2SeqTrainer(\n",
" args=training_args,\n",
" model=model,\n",
" train_dataset=vectorized_datasets[\"train\"],\n",
" eval_dataset=vectorized_datasets[\"test\"],\n",
" data_collator=data_collator,\n",
" compute_metrics=compute_metrics,\n",
" tokenizer=processor,\n",
" callbacks=[ShuffleCallback()],\n",
")"
]
},
{
"cell_type": "markdown",
"id": "67ab88c3-7091-4e51-8ad5-f5cacbe18449",
"metadata": {
"id": "67ab88c3-7091-4e51-8ad5-f5cacbe18449"
},
"source": [
"We'll save the model and processor to the output directory before training:"
]
},
{
"cell_type": "code",
"execution_count": 30,
"id": "a1ccb9ed-cbc8-4419-91c0-651e9424b672",
"metadata": {
"id": "a1ccb9ed-cbc8-4419-91c0-651e9424b672"
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"Configuration saved in ./whisper-medium-el/config.json\n",
"Model weights saved in ./whisper-medium-el/pytorch_model.bin\n",
"Feature extractor saved in ./whisper-medium-el/preprocessor_config.json\n",
"tokenizer config file saved in ./whisper-medium-el/tokenizer_config.json\n",
"Special tokens file saved in ./whisper-medium-el/special_tokens_map.json\n",
"added tokens file saved in ./whisper-medium-el/added_tokens.json\n"
]
}
],
"source": [
"model.save_pretrained(training_args.output_dir)\n",
"processor.save_pretrained(training_args.output_dir)"
]
},
{
"cell_type": "markdown",
"id": "7f404cf9-4345-468c-8196-4bd101d9bd51",
"metadata": {
"id": "7f404cf9-4345-468c-8196-4bd101d9bd51"
},
"source": [
"### Training"
]
},
{
"cell_type": "markdown",
"id": "994fcdfa-6074-4c04-96c2-ed8781c9dbc4",
"metadata": {
"id": "994fcdfa-6074-4c04-96c2-ed8781c9dbc4"
},
"source": [
"Training will take approximately 5-10 hours depending on the GPU\n",
"allocated to this Google Colab. If using this Google Colab directly to \n",
"fine-tune a Whisper model, you should make sure that training isn't \n",
"interrupted due to inactivity. A simple workaround to prevent this is \n",
"to paste the following code into the console of this tab (_right mouse click_ \n",
"-> _inspect_ -> _Console tab_ -> _insert code_)."
]
},
{
"cell_type": "markdown",
"id": "ec886310-c18d-4a8d-9d6a-842a11b22d6a",
"metadata": {
"id": "ec886310-c18d-4a8d-9d6a-842a11b22d6a"
},
"source": [
"```javascript\n",
"function ConnectButton(){\n",
" console.log(\"Connect pushed\"); \n",
" document.querySelector(\"#top-toolbar > colab-connect-button\").shadowRoot.querySelector(\"#connect\").click() \n",
"}\n",
"setInterval(ConnectButton, 60000);\n",
"```"
]
},
{
"cell_type": "markdown",
"id": "5e8b8d56-5a70-4f68-bd2e-f0752d0bd112",
"metadata": {
"id": "5e8b8d56-5a70-4f68-bd2e-f0752d0bd112"
},
"source": [
"The peak GPU memory for the given training configuration is approximately 36GB. \n",
"Depending on your GPU, it is possible that you will encounter a CUDA `\"out-of-memory\"` error when you launch training. \n",
"In this case, you can reduce the `per_device_train_batch_size` incrementally by factors of 2 \n",
"and employ [`gradient_accumulation_steps`](https://huggingface.co/docs/transformers/main_classes/trainer#transformers.Seq2SeqTrainingArguments.gradient_accumulation_steps)\n",
"to compensate.\n",
"\n",
"To launch training, simply execute:"
]
},
{
"cell_type": "code",
"execution_count": 31,
"id": "ee8b7b8e-1c9a-4d77-9137-1778a629e6de",
"metadata": {
"id": "ee8b7b8e-1c9a-4d77-9137-1778a629e6de"
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"Loading model from ./whisper-medium-el/checkpoint-6000.\n",
"The following columns in the training set don't have a corresponding argument in `WhisperForConditionalGeneration.forward` and have been ignored: input_length. If input_length are not expected by `WhisperForConditionalGeneration.forward`, you can safely ignore this message.\n",
"/home/ubuntu/.local/lib/python3.8/site-packages/transformers/optimization.py:306: FutureWarning: This implementation of AdamW is deprecated and will be removed in a future version. Use the PyTorch implementation torch.optim.AdamW instead, or set `no_deprecation_warning=True` to disable this warning\n",
" warnings.warn(\n",
"***** Running training *****\n",
" Num examples = 6428\n",
" Num Epochs = 35\n",
" Instantaneous batch size per device = 32\n",
" Total train batch size (w. parallel, distributed & accumulation) = 32\n",
" Gradient Accumulation steps = 1\n",
" Total optimization steps = 7000\n",
" Number of trainable parameters = 763857920\n",
" Continuing training from checkpoint, will skip to saved global_step\n",
" Continuing training from epoch 29\n",
" Continuing training from global step 6000\n"
]
},
{
"data": {
"text/html": [
"\n",
" \n",
" \n",
"
\n",
" [7000/7000 1:21:59, Epoch 33.98/35]\n",
"
\n",
" \n",
" \n",
" | Step | \n",
" Training Loss | \n",
" Validation Loss | \n",
" Wer | \n",
"
\n",
" \n",
" \n",
" \n",
" | 7000 | \n",
" 0.000400 | \n",
" 0.385369 | \n",
" 11.450594 | \n",
"
\n",
" \n",
"
"
],
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"The following columns in the evaluation set don't have a corresponding argument in `WhisperForConditionalGeneration.forward` and have been ignored: down_votes, locale, age, client_id, accent, input_length, gender, path, segment, up_votes. If down_votes, locale, age, client_id, accent, input_length, gender, path, segment, up_votes are not expected by `WhisperForConditionalGeneration.forward`, you can safely ignore this message.\n",
"***** Running Evaluation *****\n",
" Num examples = 1696\n",
" Batch size = 16\n",
"Saving model checkpoint to ./whisper-medium-el/checkpoint-7000\n",
"Configuration saved in ./whisper-medium-el/checkpoint-7000/config.json\n",
"Model weights saved in ./whisper-medium-el/checkpoint-7000/pytorch_model.bin\n",
"Feature extractor saved in ./whisper-medium-el/checkpoint-7000/preprocessor_config.json\n",
"tokenizer config file saved in ./whisper-medium-el/checkpoint-7000/tokenizer_config.json\n",
"Special tokens file saved in ./whisper-medium-el/checkpoint-7000/special_tokens_map.json\n",
"added tokens file saved in ./whisper-medium-el/checkpoint-7000/added_tokens.json\n",
"Feature extractor saved in ./whisper-medium-el/preprocessor_config.json\n",
"tokenizer config file saved in ./whisper-medium-el/tokenizer_config.json\n",
"Special tokens file saved in ./whisper-medium-el/special_tokens_map.json\n",
"added tokens file saved in ./whisper-medium-el/added_tokens.json\n"
]
},
{
"ename": "OSError",
"evalue": "error: insufficient permission for adding an object to repository database .git/objects\nerror: e5_interleaving-resume.ipynb: failed to insert into database\nerror: unable to index file 'e5_interleaving-resume.ipynb'\nfatal: adding files failed\n",
"output_type": "error",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mCalledProcessError\u001b[0m Traceback (most recent call last)",
"\u001b[0;32m~/.local/lib/python3.8/site-packages/huggingface_hub/repository.py\u001b[0m in \u001b[0;36mgit_add\u001b[0;34m(self, pattern, auto_lfs_track)\u001b[0m\n\u001b[1;32m 1121\u001b[0m \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1122\u001b[0;31m \u001b[0mresult\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mrun_subprocess\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"git add -v\"\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msplit\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0mpattern\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mlocal_dir\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1123\u001b[0m \u001b[0mlogger\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0minfo\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34mf\"Adding to index:\\n{result.stdout}\\n\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m~/.local/lib/python3.8/site-packages/huggingface_hub/utils/_subprocess.py\u001b[0m in \u001b[0;36mrun_subprocess\u001b[0;34m(command, folder, check, **kwargs)\u001b[0m\n\u001b[1;32m 60\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 61\u001b[0;31m return subprocess.run(\n\u001b[0m\u001b[1;32m 62\u001b[0m \u001b[0mcommand\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/usr/lib/python3.8/subprocess.py\u001b[0m in \u001b[0;36mrun\u001b[0;34m(input, capture_output, timeout, check, *popenargs, **kwargs)\u001b[0m\n\u001b[1;32m 515\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mcheck\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0mretcode\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 516\u001b[0;31m raise CalledProcessError(retcode, process.args,\n\u001b[0m\u001b[1;32m 517\u001b[0m output=stdout, stderr=stderr)\n",
"\u001b[0;31mCalledProcessError\u001b[0m: Command '['git', 'add', '-v', '.']' returned non-zero exit status 128.",
"\nDuring handling of the above exception, another exception occurred:\n",
"\u001b[0;31mOSError\u001b[0m Traceback (most recent call last)",
"\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0;31m#trainer.train()\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0mtrainer\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtrain\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mresume_from_checkpoint\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
"\u001b[0;32m~/.local/lib/python3.8/site-packages/transformers/trainer.py\u001b[0m in \u001b[0;36mtrain\u001b[0;34m(self, resume_from_checkpoint, trial, ignore_keys_for_eval, **kwargs)\u001b[0m\n\u001b[1;32m 1532\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_inner_training_loop\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_train_batch_size\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0margs\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mauto_find_batch_size\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1533\u001b[0m )\n\u001b[0;32m-> 1534\u001b[0;31m return inner_training_loop(\n\u001b[0m\u001b[1;32m 1535\u001b[0m \u001b[0margs\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1536\u001b[0m \u001b[0mresume_from_checkpoint\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mresume_from_checkpoint\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m~/.local/lib/python3.8/site-packages/transformers/trainer.py\u001b[0m in \u001b[0;36m_inner_training_loop\u001b[0;34m(self, batch_size, args, resume_from_checkpoint, trial, ignore_keys_for_eval)\u001b[0m\n\u001b[1;32m 1857\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcontrol\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcallback_handler\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mon_step_end\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstate\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcontrol\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1858\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1859\u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_maybe_log_save_evaluate\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtr_loss\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmodel\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtrial\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mepoch\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mignore_keys_for_eval\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1860\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1861\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcontrol\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcallback_handler\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mon_substep_end\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstate\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcontrol\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m~/.local/lib/python3.8/site-packages/transformers/trainer.py\u001b[0m in \u001b[0;36m_maybe_log_save_evaluate\u001b[0;34m(self, tr_loss, model, trial, epoch, ignore_keys_for_eval)\u001b[0m\n\u001b[1;32m 2124\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2125\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcontrol\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mshould_save\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2126\u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_save_checkpoint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmodel\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtrial\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmetrics\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mmetrics\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2127\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcontrol\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcallback_handler\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mon_save\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstate\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcontrol\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2128\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m~/.local/lib/python3.8/site-packages/transformers/trainer.py\u001b[0m in \u001b[0;36m_save_checkpoint\u001b[0;34m(self, model, trial, metrics)\u001b[0m\n\u001b[1;32m 2268\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2269\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpush_to_hub\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2270\u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_push_from_checkpoint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0moutput_dir\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2271\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2272\u001b[0m \u001b[0;31m# Maybe delete some older checkpoints.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m~/.local/lib/python3.8/site-packages/transformers/trainer.py\u001b[0m in \u001b[0;36m_push_from_checkpoint\u001b[0;34m(self, checkpoint_folder)\u001b[0m\n\u001b[1;32m 3440\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3441\u001b[0m \u001b[0mcommit_message\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34mf\"Training in progress, epoch {int(self.state.epoch)}\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3442\u001b[0;31m _, self.push_in_progress = self.repo.push_to_hub(\n\u001b[0m\u001b[1;32m 3443\u001b[0m \u001b[0mcommit_message\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mcommit_message\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mblocking\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mFalse\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mauto_lfs_prune\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3444\u001b[0m )\n",
"\u001b[0;32m~/.local/lib/python3.8/site-packages/huggingface_hub/repository.py\u001b[0m in \u001b[0;36mpush_to_hub\u001b[0;34m(self, commit_message, blocking, clean_ok, auto_lfs_prune)\u001b[0m\n\u001b[1;32m 1428\u001b[0m \u001b[0mlogger\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0minfo\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"Repo currently clean. Ignoring push_to_hub\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1429\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1430\u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgit_add\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mauto_lfs_track\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1431\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgit_commit\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcommit_message\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1432\u001b[0m return self.git_push(\n",
"\u001b[0;32m~/.local/lib/python3.8/site-packages/huggingface_hub/repository.py\u001b[0m in \u001b[0;36mgit_add\u001b[0;34m(self, pattern, auto_lfs_track)\u001b[0m\n\u001b[1;32m 1123\u001b[0m \u001b[0mlogger\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0minfo\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34mf\"Adding to index:\\n{result.stdout}\\n\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1124\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0msubprocess\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mCalledProcessError\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mexc\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1125\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0mEnvironmentError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mexc\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstderr\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1126\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1127\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mgit_commit\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcommit_message\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mstr\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m\"commit files to HF hub\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;31mOSError\u001b[0m: error: insufficient permission for adding an object to repository database .git/objects\nerror: e5_interleaving-resume.ipynb: failed to insert into database\nerror: unable to index file 'e5_interleaving-resume.ipynb'\nfatal: adding files failed\n"
]
}
],
"source": [
"#trainer.train()\n",
"trainer.train(resume_from_checkpoint = True)\n"
]
},
{
"cell_type": "markdown",
"id": "747c6a6e",
"metadata": {
"id": "747c6a6e",
"pycharm": {
"name": "#%% md\n"
}
},
"source": [
"(note that training may take some time to commence as we load the first training data samples with streaming mode)"
]
},
{
"cell_type": "markdown",
"id": "810ced54-7187-4a06-b2fe-ba6dcca94dc3",
"metadata": {
"id": "810ced54-7187-4a06-b2fe-ba6dcca94dc3"
},
"source": [
"We can label our checkpoint with the `whisper-event` tag on push by setting the appropriate key-word arguments (kwargs):"
]
},
{
"cell_type": "code",
"execution_count": 32,
"id": "6dd0e310-9b07-4133-ac14-2ed2d7524e22",
"metadata": {
"id": "6dd0e310-9b07-4133-ac14-2ed2d7524e22"
},
"outputs": [],
"source": [
"kwargs = {\n",
" \"dataset_tags\": \"mozilla-foundation/common_voice_11_0\",\n",
" #\"dataset_tags\": \"google/fleurs\",\n",
" \"dataset\": \"Common Voice 11.0\", # a 'pretty' name for the training dataset\n",
" #\"dataset\": \"Google FLEURS\", # a 'pretty' name for the training dataset\n",
" \"language\": \"el\",\n",
" \"model_name\": \"Whisper Medium El Greco\", # a 'pretty' name for your model\n",
" \"finetuned_from\": \"openai/whisper-medium\",\n",
" \"tasks\": \"automatic-speech-recognition\",\n",
" \"tags\": \"hf-asr-leaderboard, whisper-medium, mozilla-foundation/common_voice_11_0, greek, whisper-event\",\n",
"}"
]
},
{
"cell_type": "markdown",
"id": "090d676a-f944-4297-a938-a40eda0b2b68",
"metadata": {
"id": "090d676a-f944-4297-a938-a40eda0b2b68"
},
"source": [
"The training results can now be uploaded to the Hub. To do so, execute the `push_to_hub` command:"
]
},
{
"cell_type": "code",
"execution_count": 33,
"id": "95737cda-c5dd-4887-a4d0-dfcb0d61d977",
"metadata": {
"id": "95737cda-c5dd-4887-a4d0-dfcb0d61d977"
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"Saving model checkpoint to ./whisper-medium-el\n",
"Configuration saved in ./whisper-medium-el/config.json\n",
"Model weights saved in ./whisper-medium-el/pytorch_model.bin\n",
"Feature extractor saved in ./whisper-medium-el/preprocessor_config.json\n",
"tokenizer config file saved in ./whisper-medium-el/tokenizer_config.json\n",
"Special tokens file saved in ./whisper-medium-el/special_tokens_map.json\n",
"added tokens file saved in ./whisper-medium-el/added_tokens.json\n"
]
},
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "2cbda43ce4ff41d5b06481239fded50f",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
"Upload file pytorch_model.bin: 0%| | 32.0k/2.85G [00:00 main\n",
"\n",
"Dropping the following result as it does not have all the necessary fields:\n",
"{'task': {'name': 'Automatic Speech Recognition', 'type': 'automatic-speech-recognition'}, 'dataset': {'name': 'Common Voice 11.0', 'type': 'mozilla-foundation/common_voice_11_0', 'config': 'el', 'split': 'test', 'args': 'el'}}\n",
"To https://huggingface.co/emilios/whisper-medium-el\n",
" d6004cb..0fcacdf main -> main\n",
"\n"
]
},
{
"data": {
"text/plain": [
"'https://huggingface.co/emilios/whisper-medium-el/commit/d6004cbf9a0795ad80eecbd7642d13a34329d1ca'"
]
},
"execution_count": 33,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"trainer.push_to_hub(**kwargs)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "085a8a52-4191-4d3e-a8b2-6829d948c8b8",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"id": "82a24484-5d1a-468b-bf29-57f0a124f65e",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"id": "a7ae995c-67a9-4ded-8b61-2c22d203c7a4",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"id": "2ea7a64f-17bb-44bb-9636-66bfc10ff0d0",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"accelerator": "GPU",
"colab": {
"provenance": []
},
"gpuClass": "standard",
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.8.10"
},
"widgets": {
"application/vnd.jupyter.widget-state+json": {
"001435de01d34a339c3950dca389520d": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "HTMLModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "HTMLModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "HTMLView",
"description": "",
"description_tooltip": null,
"layout": "IPY_MODEL_cf5682dbf09c48c0bdf9e2ed3bf7b4e3",
"placeholder": "â",
"style": "IPY_MODEL_80ad52e758584edf9c63aeb23c110faa",
"value": "Download file runs/Dec06_15-14-01_132-145-142-186/1670339779.4509144/events.out.tfevents.1670339779.132-145-142-186.1786.3: 100%"
}
},
"007a9bff95c64a3689f1162efc8bdb65": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "FloatProgressModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "FloatProgressModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "ProgressView",
"bar_style": "success",
"description": "",
"description_tooltip": null,
"layout": "IPY_MODEL_7c3248075c0840b1a3e9f0afa9f46824",
"max": 3055754841,
"min": 0,
"orientation": "horizontal",
"style": "IPY_MODEL_67b5c4edf64d443ba53f6f4fbde22880",
"value": 3055754841
}
},
"0085ef5074984e37b730ce57ca37abae": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"0104836d49f140d9b522e3d17a95a8f4": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"011c4b05e4414ebfaf1a3d4e86187036": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "DescriptionStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "DescriptionStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "StyleView",
"description_width": ""
}
},
"01309ccf1d70429a82979b5023bbe0d9": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"01a0cd25ded641a1a0749e17efd8dff6": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "HTMLModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "HTMLModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "HTMLView",
"description": "",
"description_tooltip": null,
"layout": "IPY_MODEL_c98aa63bdb5c43dfb9602fc5a8a6b121",
"placeholder": "â",
"style": "IPY_MODEL_027b422ad0024d1bbc2a2372fd78e6db",
"value": "Clean file runs/Dec06_18-24-53_132-145-183-128/events.out.tfevents.1670352064.132-145-183-128.58422.0: 100%"
}
},
"027b422ad0024d1bbc2a2372fd78e6db": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "DescriptionStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "DescriptionStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "StyleView",
"description_width": ""
}
},
"02947d5ab8af45b2b561cd912a91397b": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "HBoxModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "HBoxModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "HBoxView",
"box_style": "",
"children": [
"IPY_MODEL_ee36bcc132cb403bb31427a9162efda7",
"IPY_MODEL_ef72df01007d4538aac41b5c283d40de",
"IPY_MODEL_595f2c343eb74c909c46ef89d1723e61"
],
"layout": "IPY_MODEL_bcb6f7ac5a534bfba2d2bb632de09f93"
}
},
"02da1cff196345e08466a318dd0bbcff": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "ProgressStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "ProgressStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "StyleView",
"bar_color": null,
"description_width": ""
}
},
"0486557e705347dbbba666f5e710f48f": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "DescriptionStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "DescriptionStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "StyleView",
"description_width": ""
}
},
"04a6dcd46ff04c4fa0c95b5bb32fe5a7": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "HTMLModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "HTMLModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "HTMLView",
"description": "",
"description_tooltip": null,
"layout": "IPY_MODEL_7fbdde3e90a74f89afbf1dd498140199",
"placeholder": "â",
"style": "IPY_MODEL_db037bd70f6a435e976e66b6eaf567dc",
"value": "Clean file runs/Dec06_15-27-55_132-145-142-186/1670340502.6400185/events.out.tfevents.1670340502.132-145-142-186.78108.3: 100%"
}
},
"058ef819cc6e47319bd426672d10b020": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"05a70b2994144b9f8117fe802ede63c4": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "DescriptionStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "DescriptionStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "StyleView",
"description_width": ""
}
},
"05ab4393ae0849fc887e8c767468b835": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "DescriptionStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "DescriptionStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "StyleView",
"description_width": ""
}
},
"0633200d486447ef845f060a9e184529": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "HTMLModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "HTMLModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "HTMLView",
"description": "",
"description_tooltip": null,
"layout": "IPY_MODEL_a1ef67dffc254a7fb1e60310932b68a2",
"placeholder": "â",
"style": "IPY_MODEL_de5c5a6a4b114e748e3068941e1a22fb",
"value": "Clean file runs/Dec06_15-31-50_132-145-142-186/events.out.tfevents.1670340718.132-145-142-186.170283.0: 100%"
}
},
"063b61cf67004b37944a87a245c8e22a": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"06763f89b5544e14851056fba43946ca": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "ProgressStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "ProgressStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "StyleView",
"bar_color": null,
"description_width": ""
}
},
"06ea5f4a63b44eb19eb61bc889f2eb78": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"0715b457c60a43b986c412ddbfaef501": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"075db7c06e5b4c9ba686aed5d73bc73c": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"07d61adf80824ce4bf9445f1cd0744e8": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"0898b637f8334fe491eee5836c8a9974": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "ProgressStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "ProgressStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "StyleView",
"bar_color": null,
"description_width": ""
}
},
"0a9b7eccba9a47cca67ec37eb1b79c1b": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"0abd20b47bc24b86834020dc60d527e6": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "HBoxModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "HBoxModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "HBoxView",
"box_style": "",
"children": [
"IPY_MODEL_5265abf473834cc4a03600dbbae4cde7",
"IPY_MODEL_aa0f8d0482c54b23ad5612d145e9fdcd",
"IPY_MODEL_fd303b63319b4a09bce7b21e425cf870"
],
"layout": "IPY_MODEL_746fd0c20d82434ab99faa45445208be"
}
},
"0b31da6fc8a946469ec54c1ca9b391d4": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"0ba5b19da6c84872a72e815b6193bb5f": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "HBoxModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "HBoxModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "HBoxView",
"box_style": "",
"children": [
"IPY_MODEL_9d322c207edb44d198604acb75d99120",
"IPY_MODEL_7ae857f34e77426e84090efeb8504782",
"IPY_MODEL_aa0d0ad41bfd4266af7e017a2300a7fe"
],
"layout": "IPY_MODEL_75ee3cfe47164826bc124e92f5f39c5f"
}
},
"0bbdb81f01184e68a0972fe807be7738": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"0d04712d3000439fb0ff6c6cb61816ed": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "FloatProgressModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "FloatProgressModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "ProgressView",
"bar_style": "success",
"description": "",
"description_tooltip": null,
"layout": "IPY_MODEL_f247a32acae84649b86b6e896b5b744a",
"max": 4257,
"min": 0,
"orientation": "horizontal",
"style": "IPY_MODEL_f10c7216d4174495b0a4e665c5053ac9",
"value": 4257
}
},
"0d42b72d92e849ab83a55c30475156c4": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"0daee910afee4a2ab5e7e0e0825a73f6": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"0dda93450a8f40a2b5fcacd3edefdf81": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"0eed5c11ddda42d2998a42b8e93844c2": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"0f1711f2dd254bbbac614fab33881fac": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"0f5f5674d9bb48b7b248a1f8c5e8f5bb": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "ProgressStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "ProgressStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "StyleView",
"bar_color": null,
"description_width": ""
}
},
"0f7dfe7c8f5546f2ad5b6abe41c92e0d": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"109abdd715ec40fab79875eb3c845f0b": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"128b02b070f7454b9536bdd8d7cb8c5d": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "DescriptionStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "DescriptionStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "StyleView",
"description_width": ""
}
},
"12a542c831c0422291a699807ca0cd53": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"12ff0649c9654483a40534b64dccb410": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"131c544c0b8a4d4fbb915da6d25a11d1": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "HBoxModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "HBoxModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "HBoxView",
"box_style": "",
"children": [
"IPY_MODEL_6e31091cffbe4b84900ec88314a33015",
"IPY_MODEL_c41742c414a440d4a1814e0ed76cd33b",
"IPY_MODEL_dc057697d981404aad8cff93f19c3c55"
],
"layout": "IPY_MODEL_12ff0649c9654483a40534b64dccb410"
}
},
"138eb8b7a5d14857a16216ef1427c551": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"13d6735ccabb4932b1f3a7e45f95d3f7": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "HTMLModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "HTMLModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "HTMLView",
"description": "",
"description_tooltip": null,
"layout": "IPY_MODEL_7c2830d1b05d4d38abd5f904d057ff92",
"placeholder": "â",
"style": "IPY_MODEL_128b02b070f7454b9536bdd8d7cb8c5d",
"value": " 5.62k/5.62k [08:38<00:00, 4.31B/s]"
}
},
"149481da23b04709a0f9a9a1ffb08ecf": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"14b6c40f80a34d39a2f81a43e9898ab6": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"17612db85e2b411ca6e227fb0d96f622": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "DescriptionStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "DescriptionStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "StyleView",
"description_width": ""
}
},
"18aaf26d5f5f4d00b594fdc9d4589f02": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "HTMLModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "HTMLModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "HTMLView",
"description": "",
"description_tooltip": null,
"layout": "IPY_MODEL_06ea5f4a63b44eb19eb61bc889f2eb78",
"placeholder": "â",
"style": "IPY_MODEL_cabacb3d2c654a62b03adfe4d5e5ff7e",
"value": "Download file runs/Dec06_15-31-50_132-145-142-186/1670340718.4649997/events.out.tfevents.1670340718.132-145-142-186.170283.1: 100%"
}
},
"1947a1757c724a87aff726da74058e66": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"1a0e147cb34a43b188cbfdf6956dda54": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "ProgressStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "ProgressStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "StyleView",
"bar_color": null,
"description_width": ""
}
},
"1aa0254ab8ac4f70af66ed27add0f66f": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "ProgressStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "ProgressStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "StyleView",
"bar_color": null,
"description_width": ""
}
},
"1b62af075d8b46f5a8acbe1087598f13": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "HTMLModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "HTMLModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "HTMLView",
"description": "",
"description_tooltip": null,
"layout": "IPY_MODEL_3be82e9f3c794cd78e94740205e513c5",
"placeholder": "â",
"style": "IPY_MODEL_8052181f253e4aa8840a3db3b3690855",
"value": " 17.4k/17.4k [08:40<00:00, 9.50B/s]"
}
},
"1c1ed8876d2b46d09656ffb21660579c": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "ProgressStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "ProgressStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "StyleView",
"bar_color": null,
"description_width": ""
}
},
"1cb76cca9b0041798bed7563fc373f80": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "HTMLModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "HTMLModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "HTMLView",
"description": "",
"description_tooltip": null,
"layout": "IPY_MODEL_51df0ef656c44be8a33a6cbac10983a5",
"placeholder": "â",
"style": "IPY_MODEL_6880603885a84544bf272ac3db074be1",
"value": " 4.31k/4.31k [08:37<00:00, 6.54B/s]"
}
},
"1d3d9c0936144895b6f1340ec31121cf": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"1d9849ace8e647a2b82ecb0d449ac6b0": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"1e05c9674fc04b5aa636a34af88e265d": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"1e067e32e5d647dcbc6f2a9257fec99e": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"1e2f41622c844711929a57c44a811c3e": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "HTMLModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "HTMLModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "HTMLView",
"description": "",
"description_tooltip": null,
"layout": "IPY_MODEL_97223774f78c49a18ec028ded1290426",
"placeholder": "â",
"style": "IPY_MODEL_9a1a1f9e2159477aa25e9d0af33b9ddc",
"value": " 4.16k/4.16k [08:37<00:00, 6.25B/s]"
}
},
"1e51f7e5048b464a8172f66d518abea9": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"1f0740e993014efda0e421d0d7519241": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "FloatProgressModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "FloatProgressModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "ProgressView",
"bar_style": "success",
"description": "",
"description_tooltip": null,
"layout": "IPY_MODEL_a953cb143292418993e7122a6c0e5823",
"max": 5756,
"min": 0,
"orientation": "horizontal",
"style": "IPY_MODEL_21ca425d3d76446fa0c299ae345aa674",
"value": 5756
}
},
"1f92270e2f8a45b5a38eedfd2a18c83d": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "HTMLModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "HTMLModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "HTMLView",
"description": "",
"description_tooltip": null,
"layout": "IPY_MODEL_39419a7a88474f1da5733e8e9f5a3bc7",
"placeholder": "â",
"style": "IPY_MODEL_aef4d8148e1c47f59c95fc2cf742f575",
"value": "Clean file runs/Dec06_15-40-41_132-145-142-186/1670341247.9748461/events.out.tfevents.1670341247.132-145-142-186.170283.3: 100%"
}
},
"1fdac5f458554383961fde9d003a0424": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "HBoxModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "HBoxModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "HBoxView",
"box_style": "",
"children": [
"IPY_MODEL_fccbc09015e44ea7928d200485f4ef42",
"IPY_MODEL_c34171a367cf43f391f54ccd7aec3145",
"IPY_MODEL_13d6735ccabb4932b1f3a7e45f95d3f7"
],
"layout": "IPY_MODEL_77b3e933c32d4a95a21c7851239ee6e0"
}
},
"21188bee327c4aedb689117ac9587842": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "ButtonModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "ButtonModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "ButtonView",
"button_style": "",
"description": "Login",
"disabled": false,
"icon": "",
"layout": "IPY_MODEL_a011f026bff54c2cbfcf32d839f69a38",
"style": "IPY_MODEL_c8f6afbce8ca417d979c579760fe7311",
"tooltip": ""
}
},
"218ba600e9fc488bb3bbe81a6258c5e4": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"21a1deb481b0448cb1079ff1fb968e8d": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"21ca425d3d76446fa0c299ae345aa674": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "ProgressStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "ProgressStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "StyleView",
"bar_color": null,
"description_width": ""
}
},
"2210d63c94f04880aa505e53349b811b": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "HTMLModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "HTMLModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "HTMLView",
"description": "",
"description_tooltip": null,
"layout": "IPY_MODEL_c5346e5d44a64584999b2e5471062470",
"placeholder": "â",
"style": "IPY_MODEL_dd78c7bb11fc4bc0b0dcd66ef957352a",
"value": " 10.6k/10.6k [08:40<00:00, 14.1B/s]"
}
},
"225841333b1040d687d88440b7cccd57": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"22874c3862f94d30923cc7fadd3fe38d": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"23c4f25ebdc54c2daa36cded24c02dc6": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "DescriptionStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "DescriptionStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "StyleView",
"description_width": ""
}
},
"242fce84516e453dad6a6a102d7cb781": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "HBoxModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "HBoxModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "HBoxView",
"box_style": "",
"children": [
"IPY_MODEL_01a0cd25ded641a1a0749e17efd8dff6",
"IPY_MODEL_e48b15e9785b4e8da00985487ac0aa94",
"IPY_MODEL_e27143553ccf4fdb9f077979e5ce9539"
],
"layout": "IPY_MODEL_e07314b59f454fa2959f39fc44f51e44"
}
},
"2450b049380248b498ccbfe916258252": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "HBoxModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "HBoxModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "HBoxView",
"box_style": "",
"children": [
"IPY_MODEL_f628886f29e84dbe9ad16d47d6e64188",
"IPY_MODEL_9dd9dff101d648438ee830e088ac11b8",
"IPY_MODEL_e61f9a0641774cd1889d4224da9b1689"
],
"layout": "IPY_MODEL_8416b3c8123349a9ad324a9a5be4d272"
}
},
"24af5044aa60404e8e3a8ebc2e7c98a8": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "DescriptionStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "DescriptionStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "StyleView",
"description_width": ""
}
},
"24e0e5202bbf4aeea02492497f2753e8": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "DescriptionStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "DescriptionStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "StyleView",
"description_width": ""
}
},
"25db983da4ad4196ba6a09c09ff78822": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "FloatProgressModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "FloatProgressModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "ProgressView",
"bar_style": "success",
"description": "",
"description_tooltip": null,
"layout": "IPY_MODEL_3ed4699371df40faae96325b6ddf354d",
"max": 4412,
"min": 0,
"orientation": "horizontal",
"style": "IPY_MODEL_3871dd6044cb4fa6914cb3c21d0f80dc",
"value": 4412
}
},
"26013aa0e3e246c8b1a0be1d01f7c932": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "HTMLModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "HTMLModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "HTMLView",
"description": "",
"description_tooltip": null,
"layout": "IPY_MODEL_0f7dfe7c8f5546f2ad5b6abe41c92e0d",
"placeholder": "â",
"style": "IPY_MODEL_a4e2e96150204de5bb50f1a106eb459a",
"value": "Clean file runs/Dec06_15-14-01_132-145-142-186/events.out.tfevents.1670339779.132-145-142-186.1786.2: 100%"
}
},
"2615fd5addb64b0da29c0c4f145766da": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "DescriptionStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "DescriptionStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "StyleView",
"description_width": ""
}
},
"2680836d97894f3b94e39dacbd12aace": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "HTMLModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "HTMLModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "HTMLView",
"description": "",
"description_tooltip": null,
"layout": "IPY_MODEL_058ef819cc6e47319bd426672d10b020",
"placeholder": "â",
"style": "IPY_MODEL_85609060c11a47feaa029c8c885c0729",
"value": "Clean file runs/Dec06_15-31-50_132-145-142-186/1670340718.4649997/events.out.tfevents.1670340718.132-145-142-186.170283.1: 100%"
}
},
"2752decf62464ed19611abb011700c94": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "HBoxModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "HBoxModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "HBoxView",
"box_style": "",
"children": [
"IPY_MODEL_001435de01d34a339c3950dca389520d",
"IPY_MODEL_daf9d7c783d249a1b61f5f9a50a3afd7",
"IPY_MODEL_bdac5419bfc34ba991d5f87607e88f23"
],
"layout": "IPY_MODEL_5b8df662a09a4f52bef83d59696f2357"
}
},
"27f6b46706da4b73a3e682229c68e376": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"284ee1e584ba4286816e62c19554152c": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"28e7ee736acb4e799813553496ed9ec8": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "DescriptionStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "DescriptionStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "StyleView",
"description_width": ""
}
},
"28ed16b5ef96445383137022f6ab65bd": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "FloatProgressModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "FloatProgressModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "ProgressView",
"bar_style": "success",
"description": "",
"description_tooltip": null,
"layout": "IPY_MODEL_0d42b72d92e849ab83a55c30475156c4",
"max": 4257,
"min": 0,
"orientation": "horizontal",
"style": "IPY_MODEL_a6d2fda17d9e4948848ffd175d128b2c",
"value": 4257
}
},
"2998e836efde47b088765077ea0fa10b": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"2a4751915df049f8833c70168aadbce9": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"2b15752c957a4624a8dfa7a3a9ebbe70": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "DescriptionStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "DescriptionStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "StyleView",
"description_width": ""
}
},
"2c0ca30b6d0849b68862ed297f45e456": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"2c3ec8fc9b0d453c8176c52b8dddd074": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "HTMLModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "HTMLModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "HTMLView",
"description": "",
"description_tooltip": null,
"layout": "IPY_MODEL_b54ab854ee8544a582a1fc1f7518a6c1",
"placeholder": "â",
"style": "IPY_MODEL_2ec642cf6ef741b9875f7cccf99230a1",
"value": "Download file runs/Dec06_15-22-58_132-145-142-186/events.out.tfevents.1670340186.132-145-142-186.78108.0: 100%"
}
},
"2c585ecf43fc45c5948c403a65842297": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "HTMLModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "HTMLModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "HTMLView",
"description": "",
"description_tooltip": null,
"layout": "IPY_MODEL_cdea0c411cb844fc87599aa2084d7441",
"placeholder": "â",
"style": "IPY_MODEL_59d6cb17d43940ef9c944b06ea922039",
"value": "Clean file runs/Dec06_19-00-18_132-145-183-128/events.out.tfevents.1670353243.132-145-183-128.170693.0: 100%"
}
},
"2de3a303af2d487ebe827da63e820eb5": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "HBoxModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "HBoxModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "HBoxView",
"box_style": "",
"children": [
"IPY_MODEL_4eb578564d1c43a19bdb46a3f74ac81b",
"IPY_MODEL_fe9bacb95ec446499e18f05d74347799",
"IPY_MODEL_bc5b996fefba4f30bfd4cae6047bf100"
],
"layout": "IPY_MODEL_21a1deb481b0448cb1079ff1fb968e8d"
}
},
"2e7e75bfa51c4ca292c1b5b8d19d52c4": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "FloatProgressModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "FloatProgressModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "ProgressView",
"bar_style": "success",
"description": "",
"description_tooltip": null,
"layout": "IPY_MODEL_1e05c9674fc04b5aa636a34af88e265d",
"max": 5756,
"min": 0,
"orientation": "horizontal",
"style": "IPY_MODEL_8e201b38a88e464c9a306e9e0a83e1ed",
"value": 5756
}
},
"2ec35e48e7f942a5bc26a49f5daebec9": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "HBoxModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "HBoxModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "HBoxView",
"box_style": "",
"children": [
"IPY_MODEL_dce7e355fe354c239f97ff1c05da9096",
"IPY_MODEL_d5fb639bcd354bac830ca8b59aadc6de",
"IPY_MODEL_7cf3a06b99774de9b0d4784d32bf9ef3"
],
"layout": "IPY_MODEL_aaefcf3b6cae4958bcd7a63ea39da360"
}
},
"2ec642cf6ef741b9875f7cccf99230a1": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "DescriptionStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "DescriptionStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "StyleView",
"description_width": ""
}
},
"2ecdb20e10a64692a820fa6efae6ff0a": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "DescriptionStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "DescriptionStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "StyleView",
"description_width": ""
}
},
"2f57dd6b70944ff083e6b22281a9db29": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "DescriptionStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "DescriptionStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "StyleView",
"description_width": ""
}
},
"2fb2b151ebd54ae0afc4423ebcc7a188": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"30626659e6d8486e88226467f1fbecf8": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "DescriptionStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "DescriptionStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "StyleView",
"description_width": ""
}
},
"30a74dda6a7f4b2e8e3d508f27680a1e": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "DescriptionStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "DescriptionStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "StyleView",
"description_width": ""
}
},
"30f88148fb5c4ab0b4baf54b63391ba0": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "FloatProgressModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "FloatProgressModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "ProgressView",
"bar_style": "success",
"description": "",
"description_tooltip": null,
"layout": "IPY_MODEL_284ee1e584ba4286816e62c19554152c",
"max": 5756,
"min": 0,
"orientation": "horizontal",
"style": "IPY_MODEL_9295b973124d491797fcd937e66cbb50",
"value": 5756
}
},
"31e6371eeda44771a8cecb73d1869d82": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "ProgressStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "ProgressStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "StyleView",
"bar_color": null,
"description_width": ""
}
},
"351cae6d48e64722aa420aeacf2626c3": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"3538cecbd403403d8421f1a1adddd853": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"356409f4a0ac498589c8abf6564f0aa9": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "DescriptionStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "DescriptionStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "StyleView",
"description_width": ""
}
},
"36402e96fdf440b7b5d6b16b6c6c4f92": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "HTMLModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "HTMLModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "HTMLView",
"description": "",
"description_tooltip": null,
"layout": "IPY_MODEL_a071ff14cbad4c0e8ff11573415ae815",
"placeholder": "â",
"style": "IPY_MODEL_46989affee504d00acb812ba0a69758d",
"value": " 5.62k/5.62k [08:39<00:00, 9.10B/s]"
}
},
"364adfd4a24f43f2b7c65c21928b4d1d": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "HTMLModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "HTMLModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "HTMLView",
"description": "",
"description_tooltip": null,
"layout": "IPY_MODEL_7a39271725614a07a7f8e72bab6f0e51",
"placeholder": "â",
"style": "IPY_MODEL_41b629d254014220bc76a60ffdc62b44",
"value": " 3.06G/3.06G [03:05<00:00, 16.9MB/s]"
}
},
"36c2229d260f449c979ad61adaff7707": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "ProgressStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "ProgressStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "StyleView",
"bar_color": null,
"description_width": ""
}
},
"36f255d22a5341beb926dd137d9b6dbd": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"36f2f69fbc66485b8e63bec665e76d7f": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "HTMLModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "HTMLModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "HTMLView",
"description": "",
"description_tooltip": null,
"layout": "IPY_MODEL_97a1672850aa409ea54dee1b33d191b9",
"placeholder": "â",
"style": "IPY_MODEL_b65dfe10ff294053828fde7c6dbb9b99",
"value": "Download file runs/Dec06_18-24-53_132-145-183-128/1670352064.511087/events.out.tfevents.1670352064.132-145-183-128.58422.1: 100%"
}
},
"373e453ee74e46aeb98d26b3d63a7725": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"373e4843d84941ce814fa4f1f76bee3a": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "DescriptionStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "DescriptionStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "StyleView",
"description_width": ""
}
},
"37c5f53daf16401988c6e8deff9a65fb": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"38135b51abf54c749ccb3db099f10b1d": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "DescriptionStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "DescriptionStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "StyleView",
"description_width": ""
}
},
"3839ff27494e4b6b895efebcc5cdf749": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"386fb623f71046a79df863560adf4c75": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "HTMLModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "HTMLModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "HTMLView",
"description": "",
"description_tooltip": null,
"layout": "IPY_MODEL_f3e141d28f9647f0a069ad3572a4efb2",
"placeholder": "â",
"style": "IPY_MODEL_ee0d51099a2b49ff8d0a1efee131be76",
"value": "Clean file runs/Dec06_18-51-47_132-145-183-128/events.out.tfevents.1670352720.132-145-183-128.119503.0: 100%"
}
},
"3871dd6044cb4fa6914cb3c21d0f80dc": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "ProgressStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "ProgressStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "StyleView",
"bar_color": null,
"description_width": ""
}
},
"38b759b737364aba98090b4b7ded1776": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "FloatProgressModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "FloatProgressModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "ProgressView",
"bar_style": "success",
"description": "",
"description_tooltip": null,
"layout": "IPY_MODEL_109abdd715ec40fab79875eb3c845f0b",
"max": 5756,
"min": 0,
"orientation": "horizontal",
"style": "IPY_MODEL_d7a27a0b995241a686e7d63195baa901",
"value": 5756
}
},
"39419a7a88474f1da5733e8e9f5a3bc7": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"3a0bdf5c8efe4155acffa424b00120a7": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "DescriptionStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "DescriptionStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "StyleView",
"description_width": ""
}
},
"3ae98fe05f88443d821d5df7488a123b": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "CheckboxModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "CheckboxModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "CheckboxView",
"description": "Add token as git credential?",
"description_tooltip": null,
"disabled": false,
"indent": true,
"layout": "IPY_MODEL_40d85caeaa614d918e5f199e1c5136ef",
"style": "IPY_MODEL_88dc4572ad5c495cb0489a5bc6467ee2",
"value": true
}
},
"3b187e8d68e040dabb9e00a6f7a5e7ab": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "HBoxModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "HBoxModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "HBoxView",
"box_style": "",
"children": [
"IPY_MODEL_bbf85e4741394c548136e1dc1060f03f",
"IPY_MODEL_007a9bff95c64a3689f1162efc8bdb65",
"IPY_MODEL_364adfd4a24f43f2b7c65c21928b4d1d"
],
"layout": "IPY_MODEL_d34d5eaf6bea44bbb5e9832c3d2b4c32"
}
},
"3b4a918dcadb4b18903907fcab930dfe": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "HTMLModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "HTMLModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "HTMLView",
"description": "",
"description_tooltip": null,
"layout": "IPY_MODEL_ed3ad08826e24e03ba6d611550249160",
"placeholder": "â",
"style": "IPY_MODEL_f736a64d34b94efabfdd36c297177aed",
"value": "\nPro Tip: If you don't already have one, you can create a dedicated\n'notebooks' token with 'write' access, that you can then easily reuse for all\nnotebooks.
![\"Trulli\"](\"https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/datasets/streaming.gif\")
\n",
"