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update model card README.md
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README.md
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This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.
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- F1: 0.
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## Model description
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| Training Loss | Epoch | Step | Validation Loss | F1 |
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|:-------------:|:-----:|:----:|:---------------:|:------:|
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| No log | 0.14 | 100 | 1.
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| No log | 0.28 | 200 | 1.
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| No log | 0.43 | 300 | 1.
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| No log | 0.57 | 400 | 1.
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### Framework versions
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This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.7049
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- F1: 0.5472
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## Model description
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| Training Loss | Epoch | Step | Validation Loss | F1 |
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|:-------------:|:-----:|:----:|:---------------:|:------:|
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| No log | 0.14 | 100 | 1.3954 | 0.3736 |
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| No log | 0.28 | 200 | 1.2494 | 0.4403 |
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| No log | 0.43 | 300 | 1.1859 | 0.4049 |
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| No log | 0.57 | 400 | 1.3166 | 0.4692 |
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| 1.2082 | 0.71 | 500 | 1.3011 | 0.4667 |
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| 1.2082 | 0.85 | 600 | 1.2637 | 0.4909 |
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| 1.2082 | 1.0 | 700 | 1.1596 | 0.4643 |
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| 1.2082 | 1.14 | 800 | 1.2012 | 0.4954 |
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| 1.2082 | 1.28 | 900 | 1.1207 | 0.4856 |
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| 0.9276 | 1.42 | 1000 | 1.3099 | 0.5074 |
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| 0.9276 | 1.57 | 1100 | 1.2627 | 0.4821 |
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| 0.9276 | 1.71 | 1200 | 1.1202 | 0.5034 |
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| 0.9276 | 1.85 | 1300 | 1.1611 | 0.5022 |
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| 0.9276 | 1.99 | 1400 | 1.2114 | 0.5191 |
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| 0.8288 | 2.14 | 1500 | 1.2759 | 0.5078 |
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| 0.8288 | 2.28 | 1600 | 1.3322 | 0.5286 |
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| 0.8288 | 2.42 | 1700 | 1.2991 | 0.5301 |
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| 0.8288 | 2.56 | 1800 | 1.2623 | 0.5004 |
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| 0.8288 | 2.71 | 1900 | 1.3173 | 0.5245 |
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| 0.6347 | 2.85 | 2000 | 1.3929 | 0.5318 |
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| 0.6347 | 2.99 | 2100 | 1.3334 | 0.5383 |
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| 0.6347 | 3.13 | 2200 | 1.5554 | 0.5275 |
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| 0.6347 | 3.28 | 2300 | 1.5034 | 0.5592 |
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| 0.6347 | 3.42 | 2400 | 1.5118 | 0.5716 |
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| 0.4923 | 3.56 | 2500 | 1.4939 | 0.5211 |
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| 0.4923 | 3.7 | 2600 | 1.5325 | 0.5485 |
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| 0.4923 | 3.85 | 2700 | 1.5297 | 0.5553 |
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| 0.4923 | 3.99 | 2800 | 1.5026 | 0.5420 |
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| 0.4923 | 4.13 | 2900 | 1.5561 | 0.5461 |
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| 0.3913 | 4.27 | 3000 | 1.6237 | 0.5420 |
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| 0.3913 | 4.42 | 3100 | 1.6495 | 0.5506 |
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| 0.3913 | 4.56 | 3200 | 1.7337 | 0.5502 |
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| 0.3913 | 4.7 | 3300 | 1.7264 | 0.5446 |
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| 0.3913 | 4.84 | 3400 | 1.7198 | 0.5450 |
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| 0.3154 | 4.99 | 3500 | 1.7049 | 0.5472 |
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### Framework versions
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