xlm-roberta-base-squad-32
This model is a fine-tuned version of xlm-roberta-base on the squad dataset. It achieves the following results on the evaluation set:
- Loss: 1.0083
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: 1.5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 1.0 | 350 | 1.2339 |
| 2.3864 | 2.0 | 700 | 1.0571 |
| 1.0541 | 3.0 | 1050 | 1.0246 |
| 1.0541 | 4.0 | 1400 | 0.9947 |
| 0.9214 | 5.0 | 1750 | 1.0083 |
Framework versions
- Transformers 4.18.0
- Pytorch 1.11.0+cu113
- Datasets 2.2.1
- Tokenizers 0.12.1
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