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xlm-roberta-large_ALL_BCE_NEW_data_multihead_19_shuffled_special_tokens_val

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xlm-roberta
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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_NEW_data_multihead_19_shuffled_special_tokens_val
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+ results: []
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+ ---
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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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+
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+ # xlm-roberta-large_ALL_BCE_NEW_data_multihead_19_shuffled_special_tokens_val
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+
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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: 0.8445
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+ - F1 Macro 0.1: 0.0895
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+ - F1 Macro 0.15: 0.1160
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+ - F1 Macro 0.2: 0.1402
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+ - F1 Macro 0.25: 0.1634
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+ - F1 Macro 0.3: 0.1847
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+ - F1 Macro 0.35: 0.2040
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+ - F1 Macro 0.4: 0.2229
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+ - F1 Macro 0.45: 0.2406
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+ - F1 Macro 0.5: 0.2583
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+ - F1 Macro 0.55: 0.2763
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+ - F1 Macro 0.6: 0.2924
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+ - F1 Macro 0.65: 0.3101
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+ - F1 Macro 0.7: 0.3251
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+ - F1 Macro 0.75: 0.3405
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+ - F1 Macro 0.8: 0.3547
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+ - F1 Macro 0.85: 0.3634
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+ - F1 Macro 0.9: 0.3572
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+ - F1 Macro 0.95: 0.2839
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+ - Threshold 0: 0.8
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+ - Threshold 1: 0.85
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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: 0.8
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+ - Threshold 7: 0.9
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+ - Threshold 8: 0.9
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+ - Threshold 9: 0.8
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+ - Threshold 10: 0.95
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+ - Threshold 11: 0.85
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+ - Threshold 12: 0.9
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+ - Threshold 13: 0.8
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+ - Threshold 14: 0.9
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+ - Threshold 15: 0.85
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+ - Threshold 16: 0.85
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+ - Threshold 17: 0.85
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+ - Threshold 18: 0.9
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+ - 0: 0.1543
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+ - 1: 0.2738
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+ - 2: 0.3791
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+ - 3: 0.2915
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+ - 4: 0.4439
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+ - 5: 0.4944
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+ - 6: 0.4463
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+ - 7: 0.3216
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+ - 8: 0.3402
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+ - 9: 0.5410
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+ - 10: 0.5665
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+ - 11: 0.5310
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+ - 12: 0.2331
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+ - 13: 0.1319
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+ - 14: 0.3899
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+ - 15: 0.3173
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+ - 16: 0.4432
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+ - 17: 0.6120
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+ - 18: 0.2342
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+ - Max F1: 0.3634
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+ - Mean F1: 0.3761
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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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+
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+ ### Training results
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+
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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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+ |:-------------:|:-----:|:-----:|:---------------:|:------------:|:-------------:|:------------:|:-------------:|:------------:|:-------------:|:------------:|:-------------:|:------------:|:-------------:|:------------:|:-------------:|:------------:|:-------------:|:------------:|:-------------:|:------------:|:-------------:|:-----------:|:-----------:|:-----------:|:-----------:|:-----------:|:-----------:|:-----------:|:-----------:|:-----------:|:-----------:|:------------:|:------------:|:------------:|:------------:|:------------:|:------------:|:------------:|:------------:|:------------:|:------:|:------:|:------:|:------:|:------:|:------:|:------:|:------:|:------:|:------:|:------:|:------:|:------:|:------:|:------:|:------:|:------:|:------:|:------:|:------:|:-------:|
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+ | 1.2949 | 1.0 | 5595 | 0.9920 | 0.0638 | 0.0742 | 0.0860 | 0.0994 | 0.1129 | 0.1278 | 0.1430 | 0.1589 | 0.1751 | 0.1903 | 0.2064 | 0.2235 | 0.2373 | 0.2479 | 0.2512 | 0.2275 | 0.1775 | 0.0876 | 0.75 | 0.8 | 0.75 | 0.85 | 0.65 | 0.8 | 0.75 | 0.85 | 0.8 | 0.7 | 0.9 | 0.75 | 0.8 | 0.8 | 0.85 | 0.8 | 0.85 | 0.9 | 0.85 | 0.0863 | 0.1572 | 0.2169 | 0.0959 | 0.2903 | 0.3523 | 0.3723 | 0.1624 | 0.2313 | 0.4610 | 0.3852 | 0.4756 | 0.1678 | 0.1154 | 0.2816 | 0.1848 | 0.3673 | 0.5307 | 0.1168 | 0.2512 | 0.2658 |
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+ | 0.9147 | 2.0 | 11190 | 0.9023 | 0.0813 | 0.1044 | 0.1275 | 0.1498 | 0.1706 | 0.1898 | 0.2088 | 0.2261 | 0.2449 | 0.2624 | 0.2798 | 0.2951 | 0.3107 | 0.3233 | 0.3328 | 0.3348 | 0.3156 | 0.2286 | 0.75 | 0.8 | 0.85 | 0.9 | 0.75 | 0.85 | 0.8 | 0.85 | 0.8 | 0.8 | 0.9 | 0.85 | 0.9 | 0.65 | 0.9 | 0.9 | 0.85 | 0.9 | 0.95 | 0.1231 | 0.2517 | 0.3359 | 0.2514 | 0.4106 | 0.4565 | 0.4166 | 0.2556 | 0.3152 | 0.5241 | 0.5686 | 0.5085 | 0.2177 | 0.1176 | 0.3757 | 0.3059 | 0.4286 | 0.5881 | 0.2143 | 0.3348 | 0.3508 |
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+ | 0.732 | 3.0 | 16785 | 0.8445 | 0.0895 | 0.1160 | 0.1402 | 0.1634 | 0.1847 | 0.2040 | 0.2229 | 0.2406 | 0.2583 | 0.2763 | 0.2924 | 0.3101 | 0.3251 | 0.3405 | 0.3547 | 0.3634 | 0.3572 | 0.2839 | 0.8 | 0.85 | 0.9 | 0.9 | 0.8 | 0.85 | 0.8 | 0.9 | 0.9 | 0.8 | 0.95 | 0.85 | 0.9 | 0.8 | 0.9 | 0.85 | 0.85 | 0.85 | 0.9 | 0.1543 | 0.2738 | 0.3791 | 0.2915 | 0.4439 | 0.4944 | 0.4463 | 0.3216 | 0.3402 | 0.5410 | 0.5665 | 0.5310 | 0.2331 | 0.1319 | 0.3899 | 0.3173 | 0.4432 | 0.6120 | 0.2342 | 0.3634 | 0.3761 |
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+
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+
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+ ### Framework versions
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+
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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