Training in progress epoch 0
Browse files- README.md +52 -0
- config.json +24 -0
- special_tokens_map.json +7 -0
- tf_model.h5 +3 -0
- tokenizer.json +0 -0
- tokenizer_config.json +14 -0
- vocab.txt +0 -0
README.md
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---
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tags:
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- generated_from_keras_callback
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model-index:
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- name: lmarchyok/new_results-10
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results: []
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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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# lmarchyok/new_results-10
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This model is a fine-tuned version of [pretrained_models/ClinicalBERT_1a/pytorch_model.bin](https://huggingface.co/pretrained_models/ClinicalBERT_1a/pytorch_model.bin) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Train Loss: 10.5575
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- Validation Loss: 8.7866
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- Epoch: 0
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- optimizer: {'name': 'AdamWeightDecay', 'learning_rate': {'class_name': 'WarmUp', 'config': {'initial_learning_rate': 2e-05, 'decay_schedule_fn': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': -876, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, '__passive_serialization__': True}, 'warmup_steps': 1000, 'power': 1.0, '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: mixed_float16
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### Training results
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| Train Loss | Validation Loss | Epoch |
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|:----------:|:---------------:|:-----:|
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| 10.5575 | 8.7866 | 0 |
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### Framework versions
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- Transformers 4.26.1
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- TensorFlow 2.11.0
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- Datasets 2.13.1
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- Tokenizers 0.13.2
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config.json
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{
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"_name_or_path": "pretrained_models/ClinicalBERT_1a/pytorch_model.bin",
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"architectures": [
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"BertForMaskedLM"
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],
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"attention_probs_dropout_prob": 0.1,
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"classifier_dropout": null,
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"hidden_act": "gelu",
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"hidden_dropout_prob": 0.1,
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"hidden_size": 768,
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"initializer_range": 0.02,
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"intermediate_size": 3072,
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"layer_norm_eps": 1e-12,
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"max_position_embeddings": 512,
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"model_type": "bert",
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"num_attention_heads": 12,
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"num_hidden_layers": 12,
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"pad_token_id": 0,
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"position_embedding_type": "absolute",
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"transformers_version": "4.26.1",
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"type_vocab_size": 2,
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"use_cache": true,
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"vocab_size": 24693
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}
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special_tokens_map.json
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{
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"cls_token": "[CLS]",
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"mask_token": "[MASK]",
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"pad_token": "[PAD]",
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"sep_token": "[SEP]",
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"unk_token": "[UNK]"
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}
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tf_model.h5
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version https://git-lfs.github.com/spec/v1
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oid sha256:de05f50ce5fa567003c57fe3082c83c41684fd15d6df0e953d9a8a089e62a1d9
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size 573812584
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tokenizer.json
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tokenizer_config.json
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{
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"cls_token": "[CLS]",
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"do_lower_case": false,
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"mask_token": "[MASK]",
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"model_max_length": 512,
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"name_or_path": "clinicalbert-tokenizer-new",
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"pad_token": "[PAD]",
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"sep_token": "[SEP]",
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"special_tokens_map_file": null,
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"strip_accents": null,
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"tokenize_chinese_chars": true,
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"tokenizer_class": "BertTokenizer",
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"unk_token": "[UNK]"
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}
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vocab.txt
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