output
This model is a fine-tuned version of nferruz/ProtGPT2 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.6699
- Accuracy: 0.7571
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: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- total_eval_batch_size: 2
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8.0
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
No log | 1.0 | 220 | 3.8564 | 0.4857 |
No log | 2.0 | 440 | 2.7515 | 0.6096 |
4.1568 | 3.0 | 660 | 2.2463 | 0.6780 |
4.1568 | 4.0 | 880 | 1.9817 | 0.7152 |
2.2818 | 5.0 | 1100 | 1.8278 | 0.7353 |
2.2818 | 6.0 | 1320 | 1.7313 | 0.7486 |
1.8444 | 7.0 | 1540 | 1.6847 | 0.7553 |
1.8444 | 8.0 | 1760 | 1.6699 | 0.7571 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu117
- Datasets 2.9.0
- Tokenizers 0.13.2
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