End of training
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README.md
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-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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- Accuracy: 0.
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- F1: 0.
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- Precision: 0.
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- Recall: 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 | Accuracy | F1 | Precision | Recall |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
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| 0.2221 | 3.5 | 1500 | 0.5101 | 0.8373 | 0.7940 | 0.8787 | 0.7242 |
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| 0.1545 | 4.66 | 2000 | 0.6485 | 0.8425 | 0.8101 | 0.8477 | 0.7758 |
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| 0.1178 | 5.83 | 2500 | 0.7347 | 0.8281 | 0.8024 | 0.7988 | 0.8061 |
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### Framework versions
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.3960
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- Accuracy: 0.8465
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- F1: 0.8219
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- Precision: 0.8257
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- Recall: 0.8182
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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: 3
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
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| 0.4226 | 1.17 | 500 | 0.3960 | 0.8465 | 0.8219 | 0.8257 | 0.8182 |
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| 0.309 | 2.33 | 1000 | 0.4264 | 0.8478 | 0.8226 | 0.8302 | 0.8152 |
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### Framework versions
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model.safetensors
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runs/Jan30_01-55-46_8b09110722bf/events.out.tfevents.1706580127.8b09110722bf.851.5
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