Upload TFBertForTokenClassification
Browse files- README.md +16 -67
- config.json +42 -0
- tf_model.h5 +3 -0
README.md
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---
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language:
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- tr
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license: mit
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base_model: dbmdz/bert-base-turkish-cased
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- tr
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metrics:
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- precision
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- recall
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- f1
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- accuracy
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model-index:
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- name: bert-base-turkish-cased-
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results:
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- task:
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name: Token Classification
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type: token-classification
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dataset:
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name: wikiann
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type: wikiann
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args: default
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metrics:
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- name: precision
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type: precision
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value: 0.9026122547249308
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- name: recall
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type: recall
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value: 0.9218096877305139
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- name: f1
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type: f1
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value: 0.912109968979989
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- name: accuracy
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type: accuracy
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value: 0.9604539478979423
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- task:
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name: Token Classification
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type: token-classification
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dataset:
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name: tr
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type: tr
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metrics:
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- name: precision
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type: precision
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value: 0.9026122547249308
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- name: recall
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type: recall
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value: 0.9218096877305139
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- name: f1
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type: f1
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value: 0.912109968979989
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- name: accuracy
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type: accuracy
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value: 0.9604539478979423
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---
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<!-- This model card has been generated automatically according to the information
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# bert-base-turkish-cased-
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This model is a fine-tuned version of [dbmdz/bert-base-turkish-cased](https://huggingface.co/dbmdz/bert-base-turkish-cased) on
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It achieves the following results on the evaluation set:
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- recall: 0.9218
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- f1: 0.9121
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- accuracy: 0.9605
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## Model description
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### Training hyperparameters
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The following hyperparameters were used during training:
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- fp16: True
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### Framework versions
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- Transformers 4.38.2
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- Datasets 2.18.0
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- Tokenizers 0.15.2
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---
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license: mit
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base_model: dbmdz/bert-base-turkish-cased
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tags:
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- generated_from_keras_callback
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model-index:
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- name: bert-base-turkish-cased-ner
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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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# bert-base-turkish-cased-ner
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This model is a fine-tuned version of [dbmdz/bert-base-turkish-cased](https://huggingface.co/dbmdz/bert-base-turkish-cased) on an unknown dataset.
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It achieves the following results on the evaluation set:
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## Model description
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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': 5315, '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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### Framework versions
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- Transformers 4.38.2
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- TensorFlow 2.15.0
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- Datasets 2.18.0
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- Tokenizers 0.15.2
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config.json
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{
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"_name_or_path": "dbmdz/bert-base-turkish-cased",
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"architectures": [
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"BertForTokenClassification"
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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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"id2label": {
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"0": "O",
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"1": "B-PER",
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"2": "I-PER",
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"3": "B-ORG",
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"4": "I-ORG",
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"5": "B-LOC",
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"6": "I-LOC"
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},
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"initializer_range": 0.02,
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"intermediate_size": 3072,
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"label2id": {
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"B-LOC": "5",
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"B-ORG": "3",
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"B-PER": "1",
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"I-LOC": "6",
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"I-ORG": "4",
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"I-PER": "2",
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"O": "0"
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},
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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": "4.38.2",
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"type_vocab_size": 2,
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"use_cache": true,
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"vocab_size": 32000
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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 sha256:6190a06d3ad1874aef34cf8fb9383c2b8e1aa059351b7e4eb785d92b28ff5ed6
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size 440401892
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