End of training

README.md

@@ -0,0 +1,119 @@
+---
+license: mit
+base_model: xlm-roberta-large
+tags:
+- generated_from_trainer
+model-index:
+- name: xlm-roberta-large_ALL_BCE_new_data_multihead_19_shuffled_special_tokens
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# xlm-roberta-large_ALL_BCE_new_data_multihead_19_shuffled_special_tokens
+
+This model is a fine-tuned version of [xlm-roberta-large](https://huggingface.co/xlm-roberta-large) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.8445
+- F1 Macro 0.1: 0.0895
+- F1 Macro 0.15: 0.1160
+- F1 Macro 0.2: 0.1402
+- F1 Macro 0.25: 0.1634
+- F1 Macro 0.3: 0.1847
+- F1 Macro 0.35: 0.2040
+- F1 Macro 0.4: 0.2229
+- F1 Macro 0.45: 0.2406
+- F1 Macro 0.5: 0.2583
+- F1 Macro 0.55: 0.2763
+- F1 Macro 0.6: 0.2924
+- F1 Macro 0.65: 0.3101
+- F1 Macro 0.7: 0.3251
+- F1 Macro 0.75: 0.3405
+- F1 Macro 0.8: 0.3547
+- F1 Macro 0.85: 0.3634
+- F1 Macro 0.9: 0.3572
+- F1 Macro 0.95: 0.2839
+- Threshold 0: 0.8
+- Threshold 1: 0.85
+- Threshold 2: 0.9
+- Threshold 3: 0.9
+- Threshold 4: 0.8
+- Threshold 5: 0.85
+- Threshold 6: 0.8
+- Threshold 7: 0.9
+- Threshold 8: 0.9
+- Threshold 9: 0.8
+- Threshold 10: 0.95
+- Threshold 11: 0.85
+- Threshold 12: 0.9
+- Threshold 13: 0.8
+- Threshold 14: 0.9
+- Threshold 15: 0.85
+- Threshold 16: 0.85
+- Threshold 17: 0.85
+- Threshold 18: 0.9
+- 0: 0.1543
+- 1: 0.2738
+- 2: 0.3791
+- 3: 0.2915
+- 4: 0.4439
+- 5: 0.4944
+- 6: 0.4463
+- 7: 0.3216
+- 8: 0.3402
+- 9: 0.5410
+- 10: 0.5665
+- 11: 0.5310
+- 12: 0.2331
+- 13: 0.1319
+- 14: 0.3899
+- 15: 0.3173
+- 16: 0.4432
+- 17: 0.6120
+- 18: 0.2342
+- Max F1: 0.3634
+- Mean F1: 0.3761
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 5e-06
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 2024
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 3
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| 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 |
+|:-------------:|:-----:|:-----:|:---------------:|:------------:|:-------------:|:------------:|:-------------:|:------------:|:-------------:|:------------:|:-------------:|:------------:|:-------------:|:------------:|:-------------:|:------------:|:-------------:|:------------:|:-------------:|:------------:|:-------------:|:-----------:|:-----------:|:-----------:|:-----------:|:-----------:|:-----------:|:-----------:|:-----------:|:-----------:|:-----------:|:------------:|:------------:|:------------:|:------------:|:------------:|:------------:|:------------:|:------------:|:------------:|:------:|:------:|:------:|:------:|:------:|:------:|:------:|:------:|:------:|:------:|:------:|:------:|:------:|:------:|:------:|:------:|:------:|:------:|:------:|:------:|:-------:|
+| 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  |
+| 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  |
+| 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  |
+
+
+### Framework versions
+
+- Transformers 4.36.1
+- Pytorch 2.1.0+cu121
+- Datasets 2.13.1
+- Tokenizers 0.15.0