Training in progress epoch 0
Browse files- README.md +58 -0
- config.json +53 -0
- special_tokens_map.json +7 -0
- tf_model.h5 +3 -0
- tokenizer.json +0 -0
- tokenizer_config.json +55 -0
- vocab.txt +0 -0
README.md
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---
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license: apache-2.0
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base_model: distilbert/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: aadhistii/distilbert-ner-model
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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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# aadhistii/distilbert-ner-model
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This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/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: 0.3520
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- Validation Loss: 0.3146
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- Train Precision: 0.4870
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- Train Recall: 0.1567
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- Train F1: 0.2371
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- Train Accuracy: 0.9304
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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': {'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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### Training results
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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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| 0.3520 | 0.3146 | 0.4870 | 0.1567 | 0.2371 | 0.9304 | 0 |
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### Framework versions
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- Transformers 4.41.1
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- TensorFlow 2.15.0
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- Datasets 2.19.1
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- Tokenizers 0.19.1
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config.json
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{
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"_name_or_path": "distilbert/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": "4.41.1",
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"vocab_size": 30522
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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 sha256:44b8b3060f3cb1c53037e21a42cd05476bbfef8497ccc25ad9494aef9c93842f
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size 265618704
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tokenizer.json
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tokenizer_config.json
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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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"rstrip": false,
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"single_word": false,
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"special": true
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},
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"100": {
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"content": "[UNK]",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false,
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"special": true
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},
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"101": {
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"content": "[CLS]",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false,
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"special": true
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},
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"102": {
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"content": "[SEP]",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false,
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"special": true
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},
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"103": {
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"content": "[MASK]",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": 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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}
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vocab.txt
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