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xlm-roberta-large_ALL_BCE_translated_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_translated_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_translated_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: 0.8461
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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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+
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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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+ | 1.2584 | 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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+
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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