xnli_en_lora_alpha_32_drop_01_rank_16
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: 0.4393
- Accuracy: 0.8345
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: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10.0
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
0.5297 | 1.0 | 12272 | 0.4899 | 0.8016 |
0.4893 | 2.0 | 24544 | 0.4630 | 0.8149 |
0.4588 | 3.0 | 36816 | 0.5088 | 0.7964 |
0.4506 | 4.0 | 49088 | 0.4342 | 0.8321 |
0.4258 | 5.0 | 61360 | 0.4374 | 0.8365 |
0.4064 | 6.0 | 73632 | 0.4265 | 0.8333 |
0.3795 | 7.0 | 85904 | 0.4458 | 0.8257 |
0.377 | 8.0 | 98176 | 0.4319 | 0.8337 |
0.3675 | 9.0 | 110448 | 0.4341 | 0.8373 |
0.3427 | 10.0 | 122720 | 0.4393 | 0.8345 |
Framework versions
- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.18.0
- Tokenizers 0.19.1
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