yuridrcosta
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End of training
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README.md
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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 an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.
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- Precision: 0.
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- Recall: 0.
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- F1: 0.
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- Accuracy: 0.
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## Model description
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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:
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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| 0.
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| 0.0125 | 2.0 | 1198 | 0.0184 | 0.4039 | 0.2770 | 0.3287 | 0.9958 |
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| 0.0099 | 3.0 | 1797 | 0.0141 | 0.4528 | 0.4865 | 0.4691 | 0.9958 |
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| 0.0082 | 4.0 | 2396 | 0.0279 | 0.4558 | 0.5743 | 0.5082 | 0.9958 |
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| 0.0074 | 5.0 | 2995 | 0.0138 | 0.5153 | 0.6824 | 0.5872 | 0.9960 |
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| 0.0034 | 6.0 | 3594 | 0.0193 | 0.4934 | 0.6284 | 0.5527 | 0.9953 |
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| 0.0046 | 7.0 | 4193 | 0.0190 | 0.5305 | 0.7635 | 0.6260 | 0.9960 |
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| 0.0024 | 8.0 | 4792 | 0.0286 | 0.5670 | 0.6858 | 0.6208 | 0.9955 |
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| 0.0024 | 9.0 | 5391 | 0.0270 | 0.5889 | 0.5709 | 0.5798 | 0.9953 |
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| 0.0034 | 10.0 | 5990 | 0.0339 | 0.5623 | 0.6858 | 0.6180 | 0.9953 |
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| 0.0015 | 11.0 | 6589 | 0.0373 | 0.6122 | 0.7095 | 0.6573 | 0.9947 |
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| 0.001 | 12.0 | 7188 | 0.0361 | 0.5519 | 0.6284 | 0.5877 | 0.9950 |
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| 0.0005 | 13.0 | 7787 | 0.0353 | 0.5658 | 0.6824 | 0.6187 | 0.9950 |
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| 0.0007 | 14.0 | 8386 | 0.0355 | 0.5556 | 0.7264 | 0.6296 | 0.9948 |
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| 0.0003 | 15.0 | 8985 | 0.0360 | 0.5404 | 0.7230 | 0.6185 | 0.9949 |
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### Framework versions
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- Transformers 4.
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- Pytorch 2.
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- Datasets 2.
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- Tokenizers 0.
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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 an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0008
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- Precision: 0.6804
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- Recall: 0.9301
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- F1: 0.7859
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- Accuracy: 0.9997
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## Model description
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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: 1
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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| 0.0009 | 1.0 | 3534 | 0.0008 | 0.6804 | 0.9301 | 0.7859 | 0.9997 |
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### Framework versions
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- Transformers 4.40.1
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- Pytorch 2.3.0+cu121
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- Datasets 2.19.0
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- Tokenizers 0.19.1
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model.safetensors
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