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--- |
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language: |
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- el |
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license: apache-2.0 |
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tags: |
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- whisper-event |
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- generated_from_trainer |
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datasets: |
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- mozilla-foundation/common_voice_11_0 |
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metrics: |
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- wer |
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model-index: |
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- name: whisper-sm-el-xs |
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results: |
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- task: |
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name: Automatic Speech Recognition |
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type: automatic-speech-recognition |
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dataset: |
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name: mozilla-foundation/common_voice_11_0 el |
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type: mozilla-foundation/common_voice_11_0 |
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config: el |
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split: test |
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args: el |
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metrics: |
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- name: Wer |
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type: wer |
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value: 20.63521545319465 |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# Whisper-Small (el) for Transcription |
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the mozilla-foundation/common_voice_11_0 el dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4805 |
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- Wer: 20.6352 |
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## Model description |
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This model is trained for transcription on the Greek subset on mozilla-foundation/common_voice_11_0 interleaved splits train+eval |
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## Intended uses & limitations |
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This is part of the Whisper Finetuning Event (December 2022) |
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## Training and evaluation data |
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Training used interleaved splits: train + evaluation. |
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Evaluation was done on the test split. |
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Data was streamed from Hugging Face's Hub. |
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## Training procedure |
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The script used has been uploaded in the files of this space |
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The command to run it was: |
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``` |
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python ./run_speech_recognition_seq2seq_streaming.py \ |
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--model_name_or_path "openai/whisper-small" \ |
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--model_revision "main" \ |
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--do_train True \ |
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--do_eval True \ |
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--use_auth_token False \ |
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--freeze_encoder False \ |
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--model_index_name "whisper-sm-el-xs" \ |
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--dataset_name "mozilla-foundation/common_voice_11_0" \ |
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--dataset_config_name "el" \ |
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--audio_column_name "audio" \ |
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--text_column_name "sentence" \ |
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--max_duration_in_seconds 30 \ |
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--train_split_name "train+validation" \ |
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--eval_split_name "test" \ |
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--do_lower_case False \ |
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--do_remove_punctuation False \ |
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--do_normalize_eval True \ |
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--language "greek" \ |
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--task "transcribe" \ |
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--shuffle_buffer_size 500 \ |
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--output_dir "./data/finetuningRuns/whisper-sm-el-xs" \ |
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--per_device_train_batch_size 16 \ |
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--gradient_accumulation_steps 4 \ |
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--learning_rate 1e-5 \ |
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--warmup_steps 500 \ |
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--max_steps 5000 \ |
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--gradient_checkpointing True \ |
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--fp16 True \ |
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--evaluation_strategy "steps" \ |
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--per_device_eval_batch_size 8 \ |
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--predict_with_generate True \ |
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--generation_max_length 225 \ |
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--save_steps 1000 \ |
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--eval_steps 1000 \ |
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--logging_steps 25 \ |
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--report_to "tensorboard" \ |
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--load_best_model_at_end True \ |
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--metric_for_best_model "wer" \ |
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--greater_is_better False \ |
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--push_to_hub False \ |
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--overwrite_output_dir True |
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``` |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 1e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 64 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 500 |
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- training_steps: 5000 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Wer | |
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|:-------------:|:-----:|:----:|:---------------:|:-------:| |
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| 0.0024 | 18.01 | 1000 | 0.4246 | 21.0438 | |
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| 0.0003 | 37.01 | 2000 | 0.4805 | 20.6352 | |
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| 0.0001 | 56.01 | 3000 | 0.5102 | 20.8395 | |
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| 0.0001 | 75.0 | 4000 | 0.5296 | 21.0717 | |
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| 0.0001 | 94.0 | 5000 | 0.5375 | 21.0253 | |
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Here is the summary from the log of the run: |
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``` |
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***** train metrics ***** |
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epoch = 94.0 |
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train_loss = 0.0222 |
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train_runtime = 23:06:13.19 |
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train_samples_per_second = 3.847 |
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train_steps_per_second = 0.06 |
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12/08/2022 11:20:17 - INFO - __main__ - *** Evaluate *** |
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***** eval metrics ***** |
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epoch = 94.0 |
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eval_loss = 0.4805 |
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eval_runtime = 0:23:03.68 |
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eval_samples_per_second = 1.226 |
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eval_steps_per_second = 0.153 |
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eval_wer = 20.6352 |
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Thu 08 Dec 2022 11:43:22 AM EST |
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``` |
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### Framework versions |
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- Transformers 4.26.0.dev0 |
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- Pytorch 1.13.0 |
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- Datasets 2.7.1.dev0 |
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- Tokenizers 0.12.1 |
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