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Upload TFBertForSequenceClassification

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  1. README.md +63 -0
  2. config.json +33 -0
  3. tf_model.h5 +3 -0
README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: bert-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: vc-01-bert-finetuned
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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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+ # vc-01-bert-finetuned
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+
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+ This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-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: 0.0074
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+ - Validation Loss: 0.4494
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+ - Train Recall: 0.9247
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+ - Epoch: 8
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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': 'Adam', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': True, 'is_legacy_optimizer': False, 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 7920, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
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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 Recall | Epoch |
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+ |:----------:|:---------------:|:------------:|:-----:|
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+ | 0.3152 | 0.3003 | 0.9383 | 0 |
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+ | 0.1993 | 0.2504 | 0.9036 | 1 |
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+ | 0.1250 | 0.2717 | 0.9232 | 2 |
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+ | 0.0654 | 0.3074 | 0.8870 | 3 |
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+ | 0.0347 | 0.3127 | 0.9232 | 4 |
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+ | 0.0268 | 0.4317 | 0.9217 | 5 |
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+ | 0.0146 | 0.4449 | 0.9066 | 6 |
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+ | 0.0092 | 0.4419 | 0.9066 | 7 |
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+ | 0.0074 | 0.4494 | 0.9247 | 8 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.31.0
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+ - TensorFlow 2.13.0
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+ - Datasets 2.14.4
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+ - Tokenizers 0.13.3
config.json ADDED
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+ {
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+ "_name_or_path": "bert-base-uncased",
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+ "architectures": [
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+ "BertForSequenceClassification"
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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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+ "gradient_checkpointing": false,
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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": "0",
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+ "1": "1"
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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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+ "0": 0,
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+ "1": 1
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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": "4.31.0",
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+ "type_vocab_size": 2,
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+ "use_cache": true,
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+ "vocab_size": 30522
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+ }
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