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roberta
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update model card README.md

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@@ -16,8 +16,8 @@ should probably proofread and complete it, then remove this comment. -->
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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: 0.7162
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- - F1: 0.4315
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  ## Model description
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@@ -48,30 +48,30 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|
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- | No log | 0.12 | 100 | 1.3490 | 0.0956 |
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- | No log | 0.25 | 200 | 1.4751 | 0.0956 |
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- | No log | 0.37 | 300 | 0.9687 | 0.2427 |
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- | No log | 0.49 | 400 | 1.0625 | 0.1891 |
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- | 1.2336 | 0.62 | 500 | 1.0954 | 0.1949 |
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- | 1.2336 | 0.74 | 600 | 0.9969 | 0.3080 |
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- | 1.2336 | 0.86 | 700 | 0.9171 | 0.3175 |
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- | 1.2336 | 0.99 | 800 | 0.9600 | 0.3136 |
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- | 1.2336 | 1.11 | 900 | 0.9637 | 0.3161 |
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- | 1.0269 | 1.23 | 1000 | 0.9592 | 0.3257 |
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- | 1.0269 | 1.35 | 1100 | 0.9117 | 0.3342 |
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- | 1.0269 | 1.48 | 1200 | 0.8891 | 0.3205 |
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- | 1.0269 | 1.6 | 1300 | 0.8136 | 0.3375 |
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- | 1.0269 | 1.72 | 1400 | 0.9676 | 0.3300 |
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- | 0.8592 | 1.85 | 1500 | 0.8778 | 0.3316 |
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- | 0.8592 | 1.97 | 1600 | 0.8407 | 0.3379 |
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- | 0.8592 | 2.09 | 1700 | 0.8409 | 0.3369 |
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- | 0.8592 | 2.22 | 1800 | 0.8818 | 0.3343 |
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- | 0.8592 | 2.34 | 1900 | 0.9259 | 0.3386 |
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- | 0.7521 | 2.46 | 2000 | 0.9419 | 0.3380 |
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- | 0.7521 | 2.59 | 2100 | 0.8050 | 0.3474 |
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- | 0.7521 | 2.71 | 2200 | 0.7773 | 0.4053 |
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- | 0.7521 | 2.83 | 2300 | 0.7114 | 0.4337 |
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- | 0.7521 | 2.96 | 2400 | 0.7162 | 0.4315 |
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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: 0.6271
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+ - F1: 0.6772
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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 | 0.12 | 100 | 0.7192 | 0.3792 |
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+ | No log | 0.25 | 200 | 0.7716 | 0.4005 |
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+ | No log | 0.37 | 300 | 0.7565 | 0.5297 |
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+ | No log | 0.49 | 400 | 0.5788 | 0.5806 |
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+ | 0.8223 | 0.62 | 500 | 0.5402 | 0.5933 |
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+ | 0.8223 | 0.74 | 600 | 0.5032 | 0.6666 |
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+ | 0.8223 | 0.86 | 700 | 0.4658 | 0.6754 |
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+ | 0.8223 | 0.99 | 800 | 0.5359 | 0.6441 |
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+ | 0.8223 | 1.11 | 900 | 0.5295 | 0.6442 |
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+ | 0.6009 | 1.23 | 1000 | 0.6077 | 0.6597 |
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+ | 0.6009 | 1.35 | 1100 | 0.6169 | 0.6360 |
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+ | 0.6009 | 1.48 | 1200 | 0.6014 | 0.6277 |
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+ | 0.6009 | 1.6 | 1300 | 0.6382 | 0.6327 |
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+ | 0.6009 | 1.72 | 1400 | 0.5226 | 0.6787 |
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+ | 0.5644 | 1.85 | 1500 | 0.4922 | 0.6485 |
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+ | 0.5644 | 1.97 | 1600 | 0.6181 | 0.6517 |
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+ | 0.5644 | 2.09 | 1700 | 0.6106 | 0.6781 |
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+ | 0.5644 | 2.22 | 1800 | 0.6652 | 0.6760 |
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+ | 0.5644 | 2.34 | 1900 | 0.6252 | 0.6739 |
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+ | 0.3299 | 2.46 | 2000 | 0.6620 | 0.6606 |
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+ | 0.3299 | 2.59 | 2100 | 0.6317 | 0.6772 |
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+ | 0.3299 | 2.71 | 2200 | 0.6170 | 0.6726 |
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+ | 0.3299 | 2.83 | 2300 | 0.6400 | 0.6773 |
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+ | 0.3299 | 2.96 | 2400 | 0.6271 | 0.6772 |
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  ### Framework versions