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rhaymison/bert-squad-portuguese

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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_trainer
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+ model-index:
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+ - name: finetune-BERT-squad
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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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+ # finetune-BERT-squad
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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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+ - Loss: 1.5641
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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: 2e-05
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+ - train_batch_size: 16
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+ - eval_batch_size: 16
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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: 3
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss |
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+ |:-------------:|:-----:|:-----:|:---------------:|
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+ | 2.7626 | 0.08 | 500 | 2.5754 |
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+ | 2.5464 | 0.16 | 1000 | 2.3808 |
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+ | 2.4107 | 0.24 | 1500 | 2.2688 |
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+ | 2.2761 | 0.32 | 2000 | 2.1665 |
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+ | 2.2131 | 0.41 | 2500 | 2.0738 |
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+ | 2.1205 | 0.49 | 3000 | 1.9971 |
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+ | 2.0377 | 0.57 | 3500 | 1.9840 |
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+ | 2.0069 | 0.65 | 4000 | 1.8964 |
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+ | 1.9743 | 0.73 | 4500 | 1.8704 |
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+ | 1.9438 | 0.81 | 5000 | 1.8286 |
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+ | 1.9039 | 0.89 | 5500 | 1.8021 |
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+ | 1.8537 | 0.97 | 6000 | 1.7742 |
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+ | 1.6983 | 1.06 | 6500 | 1.7601 |
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+ | 1.6149 | 1.14 | 7000 | 1.7156 |
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+ | 1.5687 | 1.22 | 7500 | 1.7334 |
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+ | 1.6083 | 1.3 | 8000 | 1.6960 |
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+ | 1.6093 | 1.38 | 8500 | 1.6979 |
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+ | 1.6001 | 1.46 | 9000 | 1.6654 |
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+ | 1.5706 | 1.54 | 9500 | 1.6478 |
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+ | 1.5379 | 1.62 | 10000 | 1.6440 |
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+ | 1.5143 | 1.7 | 10500 | 1.6111 |
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+ | 1.4894 | 1.79 | 11000 | 1.6249 |
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+ | 1.5061 | 1.87 | 11500 | 1.5881 |
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+ | 1.4999 | 1.95 | 12000 | 1.5907 |
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+ | 1.3902 | 2.03 | 12500 | 1.5939 |
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+ | 1.2689 | 2.11 | 13000 | 1.6066 |
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+ | 1.2791 | 2.19 | 13500 | 1.5989 |
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+ | 1.2811 | 2.27 | 14000 | 1.6070 |
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+ | 1.2999 | 2.35 | 14500 | 1.5910 |
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+ | 1.248 | 2.44 | 15000 | 1.6142 |
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+ | 1.2373 | 2.52 | 15500 | 1.5919 |
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+ | 1.2767 | 2.6 | 16000 | 1.5836 |
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+ | 1.2809 | 2.68 | 16500 | 1.5665 |
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+ | 1.267 | 2.76 | 17000 | 1.5690 |
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+ | 1.2798 | 2.84 | 17500 | 1.5629 |
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+ | 1.26 | 2.92 | 18000 | 1.5641 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.38.2
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+ - Pytorch 2.2.1+cu121
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+ - Datasets 2.18.0
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+ - Tokenizers 0.15.2
config.json ADDED
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+ "layer_norm_eps": 1e-12,
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+ "position_embedding_type": "absolute",
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+ "torch_dtype": "float32",
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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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