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Training in progress epoch 0

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  1. README.md +58 -0
  2. config.json +53 -0
  3. special_tokens_map.json +7 -0
  4. tf_model.h5 +3 -0
  5. tokenizer.json +0 -0
  6. tokenizer_config.json +55 -0
  7. vocab.txt +0 -0
README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: distilbert-base-uncased
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+ tags:
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+ - generated_from_keras_callback
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+ model-index:
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+ - name: Mohamedfasil/my_awesome_wnut_model
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+ results: []
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information Keras had access to. You should
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+ probably proofread and complete it, then remove this comment. -->
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+
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+ # Mohamedfasil/my_awesome_wnut_model
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+
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+ This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Train Loss: 0.1100
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+ - Validation Loss: 0.2607
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+ - Train Precision: 0.5710
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+ - Train Recall: 0.4378
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+ - Train F1: 0.4956
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+ - Train Accuracy: 0.9469
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+ - Epoch: 0
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - optimizer: {'name': 'AdamWeightDecay', 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 636, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}
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+ - training_precision: float32
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+
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+ ### Training results
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+
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+ | Train Loss | Validation Loss | Train Precision | Train Recall | Train F1 | Train Accuracy | Epoch |
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+ |:----------:|:---------------:|:---------------:|:------------:|:--------:|:--------------:|:-----:|
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+ | 0.1100 | 0.2607 | 0.5710 | 0.4378 | 0.4956 | 0.9469 | 0 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.35.2
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+ - TensorFlow 2.14.0
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+ - Datasets 2.15.0
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+ - Tokenizers 0.15.0
config.json ADDED
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+ {
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+ "_name_or_path": "distilbert-base-uncased",
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+ "activation": "gelu",
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+ "architectures": [
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+ "DistilBertForTokenClassification"
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+ ],
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+ "attention_dropout": 0.1,
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+ "dim": 768,
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+ "dropout": 0.1,
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+ "hidden_dim": 3072,
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+ "id2label": {
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+ "0": "O",
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+ "1": "B-corporation",
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+ "2": "I-corporation",
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+ "3": "B-creative-work",
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+ "4": "I-creative-work",
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+ "5": "B-group",
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+ "6": "I-group",
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+ "7": "B-location",
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+ "8": "I-location",
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+ "9": "B-person",
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+ "10": "I-person",
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+ "11": "B-product",
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+ "12": "I-product"
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+ },
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+ "initializer_range": 0.02,
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+ "label2id": {
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+ "B-corporation": 1,
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+ "B-creative-work": 3,
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+ "B-group": 5,
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+ "B-location": 7,
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+ "B-person": 9,
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+ "B-product": 11,
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+ "I-corporation": 2,
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+ "I-creative-work": 4,
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+ "I-group": 6,
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+ "I-location": 8,
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+ "I-person": 10,
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+ "I-product": 12,
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+ "O": 0
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+ },
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+ "max_position_embeddings": 512,
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+ "model_type": "distilbert",
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+ "n_heads": 12,
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+ "n_layers": 6,
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+ "pad_token_id": 0,
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+ "qa_dropout": 0.1,
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+ "seq_classif_dropout": 0.2,
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+ "sinusoidal_pos_embds": false,
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+ "tie_weights_": true,
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+ "transformers_version": "4.35.2",
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+ "vocab_size": 30522
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+ }
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+ {
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+ "sep_token": "[SEP]",
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+ "unk_token": "[UNK]"
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+ }
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tokenizer.json ADDED
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tokenizer_config.json ADDED
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+ {
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+ "added_tokens_decoder": {
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+ "0": {
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+ "content": "[PAD]",
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+ "lstrip": false,
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+ "normalized": false,
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+ "special": true
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+ }
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+ },
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+ "clean_up_tokenization_spaces": true,
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+ "cls_token": "[CLS]",
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+ "do_lower_case": true,
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+ "mask_token": "[MASK]",
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+ "model_max_length": 512,
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+ "pad_token": "[PAD]",
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+ "sep_token": "[SEP]",
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+ "strip_accents": null,
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+ "tokenize_chinese_chars": true,
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+ "tokenizer_class": "DistilBertTokenizer",
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+ "unk_token": "[UNK]"
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+ }
vocab.txt ADDED
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