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--- |
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license: mit |
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base_model: xlm-roberta-large |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: xlm-roberta-large_ALL_BCE_translated_data_multihead_19_shuffled_special_tokens_val |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# xlm-roberta-large_ALL_BCE_translated_data_multihead_19_shuffled_special_tokens_val |
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This model is a fine-tuned version of [xlm-roberta-large](https://huggingface.co/xlm-roberta-large) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.8461 |
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- F1 Macro 0.1: 0.0910 |
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- F1 Macro 0.15: 0.1188 |
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- F1 Macro 0.2: 0.1445 |
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- F1 Macro 0.25: 0.1675 |
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- F1 Macro 0.3: 0.1890 |
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- F1 Macro 0.35: 0.2092 |
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- F1 Macro 0.4: 0.2277 |
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- F1 Macro 0.45: 0.2467 |
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- F1 Macro 0.5: 0.2641 |
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- F1 Macro 0.55: 0.2816 |
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- F1 Macro 0.6: 0.2976 |
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- F1 Macro 0.65: 0.3120 |
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- F1 Macro 0.7: 0.3274 |
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- F1 Macro 0.75: 0.3429 |
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- F1 Macro 0.8: 0.3559 |
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- F1 Macro 0.85: 0.3640 |
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- F1 Macro 0.9: 0.3511 |
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- F1 Macro 0.95: 0.2837 |
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- Threshold 0: 0.8 |
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- Threshold 1: 0.8 |
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- Threshold 2: 0.9 |
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- Threshold 3: 0.9 |
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- Threshold 4: 0.8 |
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- Threshold 5: 0.85 |
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- Threshold 6: 0.75 |
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- Threshold 7: 0.85 |
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- Threshold 8: 0.8 |
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- Threshold 9: 0.75 |
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- Threshold 10: 0.9 |
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- Threshold 11: 0.85 |
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- Threshold 12: 0.9 |
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- Threshold 13: 0.85 |
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- Threshold 14: 0.9 |
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- Threshold 15: 0.9 |
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- Threshold 16: 0.85 |
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- Threshold 17: 0.8 |
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- Threshold 18: 0.9 |
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- 0: 0.1473 |
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- 1: 0.2629 |
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- 2: 0.3389 |
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- 3: 0.2821 |
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- 4: 0.4463 |
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- 5: 0.4627 |
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- 6: 0.4396 |
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- 7: 0.3159 |
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- 8: 0.3574 |
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- 9: 0.5352 |
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- 10: 0.5231 |
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- 11: 0.5417 |
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- 12: 0.2511 |
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- 13: 0.1600 |
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- 14: 0.3940 |
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- 15: 0.3114 |
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- 16: 0.4335 |
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- 17: 0.6149 |
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- 18: 0.2350 |
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- Max F1: 0.3640 |
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- Mean F1: 0.3712 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-06 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 2024 |
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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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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 3 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | F1 Macro 0.1 | F1 Macro 0.15 | F1 Macro 0.2 | F1 Macro 0.25 | F1 Macro 0.3 | F1 Macro 0.35 | F1 Macro 0.4 | F1 Macro 0.45 | F1 Macro 0.5 | F1 Macro 0.55 | F1 Macro 0.6 | F1 Macro 0.65 | F1 Macro 0.7 | F1 Macro 0.75 | F1 Macro 0.8 | F1 Macro 0.85 | F1 Macro 0.9 | F1 Macro 0.95 | Threshold 0 | Threshold 1 | Threshold 2 | Threshold 3 | Threshold 4 | Threshold 5 | Threshold 6 | Threshold 7 | Threshold 8 | Threshold 9 | Threshold 10 | Threshold 11 | Threshold 12 | Threshold 13 | Threshold 14 | Threshold 15 | Threshold 16 | Threshold 17 | Threshold 18 | 0 | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | 14 | 15 | 16 | 17 | 18 | Max F1 | Mean F1 | |
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| 1.2584 | 1.0 | 5595 | 0.9674 | 0.0635 | 0.0727 | 0.0841 | 0.0965 | 0.1097 | 0.1230 | 0.1373 | 0.1527 | 0.1683 | 0.1848 | 0.2014 | 0.2169 | 0.2332 | 0.2464 | 0.2560 | 0.2481 | 0.2156 | 0.1188 | 0.6 | 0.75 | 0.85 | 0.85 | 0.75 | 0.75 | 0.85 | 0.85 | 0.8 | 0.75 | 0.9 | 0.8 | 0.9 | 0.9 | 0.9 | 0.85 | 0.85 | 0.95 | 0.85 | 0.0616 | 0.1640 | 0.2570 | 0.1316 | 0.3160 | 0.3605 | 0.3737 | 0.1615 | 0.2401 | 0.4683 | 0.3648 | 0.4699 | 0.1921 | 0.1682 | 0.2660 | 0.1916 | 0.3389 | 0.5671 | 0.1519 | 0.2560 | 0.2760 | |
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| 0.8825 | 2.0 | 11190 | 0.8752 | 0.0809 | 0.1031 | 0.1250 | 0.1462 | 0.1660 | 0.1849 | 0.2037 | 0.2222 | 0.2378 | 0.2545 | 0.2731 | 0.2904 | 0.3086 | 0.3270 | 0.3385 | 0.3475 | 0.3283 | 0.2515 | 0.85 | 0.8 | 0.85 | 0.85 | 0.8 | 0.85 | 0.85 | 0.85 | 0.8 | 0.75 | 0.9 | 0.85 | 0.85 | 0.75 | 0.9 | 0.9 | 0.85 | 0.85 | 0.9 | 0.1324 | 0.2436 | 0.3250 | 0.2624 | 0.4264 | 0.4417 | 0.4149 | 0.2962 | 0.3592 | 0.5202 | 0.5151 | 0.5290 | 0.2303 | 0.1584 | 0.3684 | 0.2897 | 0.4175 | 0.6251 | 0.2145 | 0.3475 | 0.3563 | |
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| 0.7223 | 3.0 | 16785 | 0.8461 | 0.0910 | 0.1188 | 0.1445 | 0.1675 | 0.1890 | 0.2092 | 0.2277 | 0.2467 | 0.2641 | 0.2816 | 0.2976 | 0.3120 | 0.3274 | 0.3429 | 0.3559 | 0.3640 | 0.3511 | 0.2837 | 0.8 | 0.8 | 0.9 | 0.9 | 0.8 | 0.85 | 0.75 | 0.85 | 0.8 | 0.75 | 0.9 | 0.85 | 0.9 | 0.85 | 0.9 | 0.9 | 0.85 | 0.8 | 0.9 | 0.1473 | 0.2629 | 0.3389 | 0.2821 | 0.4463 | 0.4627 | 0.4396 | 0.3159 | 0.3574 | 0.5352 | 0.5231 | 0.5417 | 0.2511 | 0.1600 | 0.3940 | 0.3114 | 0.4335 | 0.6149 | 0.2350 | 0.3640 | 0.3712 | |
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### Framework versions |
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- Transformers 4.36.1 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.13.1 |
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- Tokenizers 0.15.0 |
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