deberta-semeval25_EN08_fold3
This model is a fine-tuned version of microsoft/deberta-v3-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 9.1157
- Precision Samples: 0.1421
- Recall Samples: 0.5756
- F1 Samples: 0.2085
- Precision Macro: 0.7606
- Recall Macro: 0.3423
- F1 Macro: 0.2156
- Precision Micro: 0.1314
- Recall Micro: 0.4788
- F1 Micro: 0.2062
- Precision Weighted: 0.4667
- Recall Weighted: 0.4788
- F1 Weighted: 0.1520
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: 2e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10
Training results
Training Loss | Epoch | Step | Validation Loss | Precision Samples | Recall Samples | F1 Samples | Precision Macro | Recall Macro | F1 Macro | Precision Micro | Recall Micro | F1 Micro | Precision Weighted | Recall Weighted | F1 Weighted |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
11.095 | 1.0 | 19 | 10.6400 | 1.0 | 0.0 | 0.0 | 1.0 | 0.1556 | 0.1556 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 |
10.2278 | 2.0 | 38 | 10.2333 | 0.1374 | 0.3013 | 0.1697 | 0.9615 | 0.1926 | 0.1657 | 0.1442 | 0.1785 | 0.1595 | 0.8356 | 0.1785 | 0.0527 |
9.5925 | 3.0 | 57 | 9.9327 | 0.1375 | 0.3699 | 0.1830 | 0.9031 | 0.2134 | 0.1735 | 0.1336 | 0.2408 | 0.1719 | 0.6911 | 0.2408 | 0.0774 |
8.9765 | 4.0 | 76 | 9.6535 | 0.1451 | 0.4784 | 0.2044 | 0.8754 | 0.2701 | 0.1879 | 0.1362 | 0.3711 | 0.1992 | 0.6423 | 0.3711 | 0.1069 |
9.0712 | 5.0 | 95 | 9.4718 | 0.1306 | 0.5154 | 0.1935 | 0.8449 | 0.2948 | 0.1925 | 0.1264 | 0.4079 | 0.1930 | 0.5821 | 0.4079 | 0.1145 |
8.8157 | 6.0 | 114 | 9.2988 | 0.1297 | 0.5550 | 0.1938 | 0.8061 | 0.3186 | 0.2014 | 0.1247 | 0.4561 | 0.1959 | 0.5153 | 0.4561 | 0.1305 |
9.2663 | 7.0 | 133 | 9.3128 | 0.1386 | 0.5483 | 0.2044 | 0.7855 | 0.3211 | 0.2127 | 0.1323 | 0.4504 | 0.2045 | 0.4887 | 0.4504 | 0.1487 |
8.1988 | 8.0 | 152 | 9.1760 | 0.1436 | 0.5540 | 0.2084 | 0.7656 | 0.3217 | 0.2097 | 0.1331 | 0.4561 | 0.2060 | 0.4778 | 0.4561 | 0.1483 |
8.7719 | 9.0 | 171 | 9.1413 | 0.1400 | 0.5696 | 0.2045 | 0.7801 | 0.3316 | 0.2110 | 0.1295 | 0.4674 | 0.2028 | 0.4820 | 0.4674 | 0.1482 |
8.6954 | 10.0 | 190 | 9.1157 | 0.1421 | 0.5756 | 0.2085 | 0.7606 | 0.3423 | 0.2156 | 0.1314 | 0.4788 | 0.2062 | 0.4667 | 0.4788 | 0.1520 |
Framework versions
- Transformers 4.46.0
- Pytorch 2.3.1
- Datasets 2.21.0
- Tokenizers 0.20.1
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Base model
microsoft/deberta-v3-base