xnli_en_lora_alpha_64_drop_0.1_rank_32_seed_123
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: 0.4468
- Accuracy: 0.8373
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: 123
- 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 |
---|---|---|---|---|
0.5387 | 1.0 | 12272 | 0.5101 | 0.8076 |
0.5105 | 2.0 | 24544 | 0.4710 | 0.8064 |
0.4686 | 3.0 | 36816 | 0.4535 | 0.8253 |
0.4378 | 4.0 | 49088 | 0.4549 | 0.8237 |
0.4351 | 5.0 | 61360 | 0.4700 | 0.8133 |
0.4127 | 6.0 | 73632 | 0.4477 | 0.8345 |
0.3766 | 7.0 | 85904 | 0.4446 | 0.8333 |
0.3602 | 8.0 | 98176 | 0.4504 | 0.8369 |
0.3441 | 9.0 | 110448 | 0.4440 | 0.8378 |
0.3256 | 10.0 | 122720 | 0.4468 | 0.8373 |
Framework versions
- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.18.0
- Tokenizers 0.19.1
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