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End of training

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  1. README.md +56 -0
  2. config.json +25 -0
  3. special_tokens_map.json +7 -0
  4. tf_model.h5 +3 -0
  5. tokenizer.json +0 -0
  6. tokenizer_config.json +14 -0
  7. vocab.txt +0 -0
README.md ADDED
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+ ---
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+ license: apache-2.0
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+ tags:
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+ - generated_from_keras_callback
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+ model-index:
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+ - name: prahlad/rotten_model
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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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+ # prahlad/rotten_model
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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: 0.2232
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+ - Train Accuracy: 0.9121
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+ - Validation Loss: 0.4083
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+ - Validation Accuracy: 0.8340
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+ - Epoch: 1
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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', 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 5e-05, 'decay_steps': 12795, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, '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 | Train Accuracy | Validation Loss | Validation Accuracy | Epoch |
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+ |:----------:|:--------------:|:---------------:|:-------------------:|:-----:|
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+ | 0.4619 | 0.7877 | 0.7007 | 0.7280 | 0 |
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+ | 0.2232 | 0.9121 | 0.4083 | 0.8340 | 1 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.20.1
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+ - TensorFlow 2.8.2
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+ - Datasets 2.3.2
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+ - Tokenizers 0.12.1
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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+ "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": "4.20.1",
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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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+ }
special_tokens_map.json ADDED
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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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+ }
tf_model.h5 ADDED
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tokenizer.json ADDED
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tokenizer_config.json ADDED
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+ {
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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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+ "name_or_path": "bert-base-uncased",
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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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+ }
vocab.txt ADDED
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