fine-tuned-QAS-Squad_2-with-xlm-roberta-large
This model is a fine-tuned version of xlm-roberta-large on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.8615
- Exact Match: 69.2340
- F1: 82.5542
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: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Exact Match | F1 |
|---|---|---|---|---|---|
| 1.0967 | 0.5 | 464 | 1.0076 | 57.8908 | 71.8971 |
| 0.912 | 1.0 | 928 | 0.8118 | 65.0306 | 79.0193 |
| 0.8071 | 1.5 | 1392 | 0.7587 | 67.2288 | 80.3986 |
| 0.7414 | 2.0 | 1856 | 0.7322 | 68.3614 | 81.3949 |
| 0.6548 | 2.5 | 2320 | 0.7685 | 67.5896 | 81.3012 |
| 0.624 | 3.0 | 2784 | 0.7307 | 68.5544 | 82.0875 |
| 0.5412 | 3.5 | 3248 | 0.7606 | 69.2340 | 82.4384 |
| 0.5356 | 4.0 | 3712 | 0.7352 | 69.5612 | 82.7509 |
| 0.4463 | 4.5 | 4176 | 0.7862 | 69.2843 | 82.3298 |
| 0.4899 | 5.0 | 4640 | 0.7868 | 69.5109 | 82.7397 |
| 0.417 | 5.5 | 5104 | 0.8615 | 69.2340 | 82.5542 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu117
- Datasets 2.2.0
- Tokenizers 0.13.2
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