xnli_en_lora_alpha_32_drop_0.1_rank_16_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: 0.4364
- Accuracy: 0.8369
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 |
---|---|---|---|---|
0.533 | 1.0 | 12272 | 0.5118 | 0.8068 |
0.499 | 2.0 | 24544 | 0.4688 | 0.8161 |
0.4658 | 3.0 | 36816 | 0.4617 | 0.8205 |
0.433 | 4.0 | 49088 | 0.4578 | 0.8261 |
0.4299 | 5.0 | 61360 | 0.4438 | 0.8233 |
0.4133 | 6.0 | 73632 | 0.4287 | 0.8321 |
0.386 | 7.0 | 85904 | 0.4503 | 0.8285 |
0.3713 | 8.0 | 98176 | 0.4415 | 0.8325 |
0.3653 | 9.0 | 110448 | 0.4384 | 0.8341 |
0.3559 | 10.0 | 122720 | 0.4364 | 0.8369 |
Framework versions
- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.18.0
- Tokenizers 0.19.1
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