xnli_en_adalora_alpha_32_drop_0.1_rank_16_seed_456
This model is a fine-tuned version of xlm-roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4229
- Accuracy: 0.8422
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: 0.0003
- train_batch_size: 32
- eval_batch_size: 8
- seed: 456
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15.0
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
0.5578 | 1.0 | 12272 | 0.4910 | 0.8141 |
0.5214 | 2.0 | 24544 | 0.4890 | 0.8092 |
0.4988 | 3.0 | 36816 | 0.4566 | 0.8197 |
0.474 | 4.0 | 49088 | 0.4239 | 0.8313 |
0.4507 | 5.0 | 61360 | 0.4231 | 0.8345 |
0.4372 | 6.0 | 73632 | 0.4308 | 0.8293 |
0.4327 | 7.0 | 85904 | 0.4284 | 0.8353 |
0.4129 | 8.0 | 98176 | 0.4191 | 0.8325 |
0.4194 | 9.0 | 110448 | 0.4322 | 0.8333 |
0.4077 | 10.0 | 122720 | 0.4314 | 0.8365 |
0.3929 | 11.0 | 134992 | 0.4233 | 0.8422 |
0.3918 | 12.0 | 147264 | 0.4155 | 0.8442 |
0.3884 | 13.0 | 159536 | 0.4405 | 0.8317 |
0.3798 | 14.0 | 171808 | 0.4226 | 0.8442 |
0.3853 | 15.0 | 184080 | 0.4229 | 0.8422 |
Framework versions
- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.18.0
- Tokenizers 0.19.1
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