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End of training

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README.md ADDED
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+ ---
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+ license: mit
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+ base_model: neuralmind/bert-base-portuguese-cased
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - accuracy
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+ model-index:
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+ - name: bert_ENEM
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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 the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # bert_ENEM
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+
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+ This model is a fine-tuned version of [neuralmind/bert-base-portuguese-cased](https://huggingface.co/neuralmind/bert-base-portuguese-cased) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 3.0267
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+ - Accuracy: 0.3611
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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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+ - learning_rate: 5e-05
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+ - train_batch_size: 3
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+ - eval_batch_size: 2
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+ - seed: 42
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: linear
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+ - num_epochs: 10
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | No log | 1.0 | 107 | 1.6131 | 0.25 |
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+ | No log | 2.0 | 214 | 1.5635 | 0.3333 |
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+ | No log | 3.0 | 321 | 1.4007 | 0.4444 |
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+ | No log | 4.0 | 428 | 1.9448 | 0.4167 |
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+ | 1.137 | 5.0 | 535 | 2.1251 | 0.4167 |
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+ | 1.137 | 6.0 | 642 | 2.4106 | 0.3889 |
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+ | 1.137 | 7.0 | 749 | 2.5102 | 0.3333 |
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+ | 1.137 | 8.0 | 856 | 2.6479 | 0.4167 |
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+ | 1.137 | 9.0 | 963 | 2.9045 | 0.3889 |
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+ | 0.0629 | 10.0 | 1070 | 3.0267 | 0.3611 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.35.2
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+ - Pytorch 2.1.1
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+ - Datasets 2.15.0
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+ - Tokenizers 0.15.0
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+ ],
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+ "directionality": "bidi",
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+ "initializer_range": 0.02,
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+ "layer_norm_eps": 1e-12,
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+ "model_type": "bert",
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+ "num_attention_heads": 12,
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+ "pooler_type": "first_token_transform",
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+ "position_embedding_type": "absolute",
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.35.2",
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+ "type_vocab_size": 2,
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+ }
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