Model save
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README.md
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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: 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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The following hyperparameters were used during training:
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- learning_rate: 2e-05
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- train_batch_size:
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- eval_batch_size:
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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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| 0.2056 | 4.0 | 1252 | 0.2222 | 0.9410 | 0.9416 | 0.9413 | 0.9374 |
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### Framework versions
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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: 0.2128
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- Precision: 0.9438
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- Recall: 0.9453
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- F1: 0.9446
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- Accuracy: 0.9412
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## Model description
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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: 32
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- eval_batch_size: 32
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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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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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| 0.5739 | 1.0 | 625 | 0.2622 | 0.9206 | 0.9248 | 0.9227 | 0.9207 |
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| 0.2568 | 2.0 | 1250 | 0.2129 | 0.9382 | 0.9452 | 0.9417 | 0.9385 |
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| 0.1837 | 3.0 | 1875 | 0.2128 | 0.9438 | 0.9453 | 0.9446 | 0.9412 |
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### Framework versions
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model.safetensors
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