rinna-arabert22-qa-ar2
This model is a fine-tuned version of aubmindlab/araelectra-base-discriminator on the arcd dataset. It achieves the following results on the evaluation set:
- Loss: 5.9506
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: 0.001
- train_batch_size: 2
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 100
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 4.412 | 6.92 | 150 | 5.9506 |
| 5.9523 | 13.83 | 300 | 5.9506 |
| 5.9551 | 20.75 | 450 | 5.9506 |
| 5.952 | 27.67 | 600 | 5.9506 |
| 5.9518 | 34.58 | 750 | 5.9506 |
| 5.9501 | 41.5 | 900 | 5.9506 |
| 5.9526 | 48.41 | 1050 | 5.9506 |
| 5.9538 | 55.33 | 1200 | 5.9506 |
| 5.9517 | 62.25 | 1350 | 5.9506 |
| 5.9529 | 69.16 | 1500 | 5.9506 |
| 5.9518 | 76.08 | 1650 | 5.9506 |
| 5.9532 | 83.0 | 1800 | 5.9506 |
| 5.9518 | 89.91 | 1950 | 5.9506 |
| 5.9515 | 96.83 | 2100 | 5.9506 |
Framework versions
- Transformers 4.32.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3
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