deberta-base.as.finetuned
This model is a fine-tuned version of on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 5.9191
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: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
6.6297 | 0.46 | 1000 | 6.5539 |
6.4688 | 0.92 | 2000 | 6.4491 |
6.3844 | 1.38 | 3000 | 6.3672 |
6.3167 | 1.84 | 4000 | 6.2918 |
6.252 | 2.3 | 5000 | 6.2378 |
6.2027 | 2.76 | 6000 | 6.1876 |
6.1586 | 3.22 | 7000 | 6.1400 |
6.1194 | 3.68 | 8000 | 6.1085 |
6.0882 | 4.14 | 9000 | 6.0751 |
6.0543 | 4.6 | 10000 | 6.0519 |
6.023 | 5.06 | 11000 | 6.0291 |
6.0118 | 5.52 | 12000 | 6.0053 |
5.9866 | 5.98 | 13000 | 5.9925 |
5.9737 | 6.44 | 14000 | 5.9772 |
5.9609 | 6.9 | 15000 | 5.9589 |
5.9537 | 7.36 | 16000 | 5.9472 |
5.9366 | 7.82 | 17000 | 5.9419 |
5.9282 | 8.28 | 18000 | 5.9283 |
5.926 | 8.74 | 19000 | 5.9246 |
5.9194 | 9.2 | 20000 | 5.9283 |
5.9172 | 9.66 | 21000 | 5.9273 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu118
- Datasets 2.17.1
- Tokenizers 0.15.2
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