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Semhal2024
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emotion-model11_0

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Safetensors
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Semhal2024/emotion-model3_fold_0

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  1. README.md +13 -13
  2. adapter_model.safetensors +1 -1
README.md CHANGED
@@ -19,9 +19,9 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.0583
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- - Accuracy: 0.5828
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- - F1: 0.5244
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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- | No log | 1.0 | 41 | 1.3349 | 0.3804 | 0.2096 |
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- | 1.3438 | 2.0 | 82 | 1.2443 | 0.3804 | 0.2096 |
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- | 1.2717 | 3.0 | 123 | 1.0583 | 0.5828 | 0.5244 |
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- | 1.1723 | 4.0 | 164 | 1.0449 | 0.5215 | 0.3965 |
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- | 1.1136 | 5.0 | 205 | 0.9935 | 0.5521 | 0.4423 |
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- | 1.1136 | 6.0 | 246 | 0.9746 | 0.5890 | 0.5003 |
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- | 1.1124 | 7.0 | 287 | 0.9637 | 0.5890 | 0.5003 |
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- | 1.0842 | 8.0 | 328 | 0.9562 | 0.5767 | 0.4846 |
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- | 1.0456 | 9.0 | 369 | 0.9516 | 0.5767 | 0.4837 |
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- | 1.0552 | 10.0 | 410 | 0.9428 | 0.5767 | 0.4837 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.9531
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+ - Accuracy: 0.6135
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+ - F1: 0.5573
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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+ | No log | 1.0 | 41 | 1.3368 | 0.3804 | 0.2096 |
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+ | 1.3413 | 2.0 | 82 | 1.2883 | 0.3804 | 0.2096 |
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+ | 1.2917 | 3.0 | 123 | 1.0577 | 0.5521 | 0.4841 |
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+ | 1.1702 | 4.0 | 164 | 1.0247 | 0.5337 | 0.4033 |
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+ | 1.1099 | 5.0 | 205 | 0.9804 | 0.5460 | 0.4324 |
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+ | 1.1099 | 6.0 | 246 | 0.9531 | 0.6135 | 0.5573 |
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+ | 1.0856 | 7.0 | 287 | 0.9336 | 0.6135 | 0.5301 |
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+ | 1.0752 | 8.0 | 328 | 0.9257 | 0.5767 | 0.4883 |
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+ | 1.0393 | 9.0 | 369 | 0.9182 | 0.5828 | 0.5188 |
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+ | 1.0449 | 10.0 | 410 | 0.9131 | 0.5828 | 0.5188 |
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  ### Framework versions
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