bhattronak
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Training in progress epoch 0
Browse files- README.md +56 -0
- config.json +1 -1
- 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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tags:
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- generated_from_keras_callback
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model-index:
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- name: bhattronak/my-awesome-address-tokenizer-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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# bhattronak/my-awesome-address-tokenizer-model
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This model was trained from scratch on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Train Loss: 1.1892
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- Validation Loss: 0.6671
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- Train Precision: 0.7283
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- Train Recall: 0.7609
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- Train F1: 0.7442
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- Train Accuracy: 0.7679
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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': 489, '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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| 1.1892 | 0.6671 | 0.7283 | 0.7609 | 0.7442 | 0.7679 | 0 |
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### Framework versions
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- Transformers 4.35.0
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- TensorFlow 2.14.0
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- Datasets 2.14.6
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- Tokenizers 0.14.1
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config.json
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{
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"_name_or_path": "
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"activation": "gelu",
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"architectures": [
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"DistilBertForTokenClassification"
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{
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"_name_or_path": "bhattronak/my-awesome-address-tokenizer-model",
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"activation": "gelu",
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"architectures": [
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"DistilBertForTokenClassification"
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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:a13f59b6e44ec45df0309f94e1344e4831816bf64437e13114df28e4949897e0
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size 265624848
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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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