gpt2_SMILES_bpe_combined_step1_3
This model is a fine-tuned version of gpt2 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5978
- Accuracy: 0.8057
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: 16
- eval_batch_size: 16
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- total_train_batch_size: 128
- total_eval_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10.0
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
0.7137 | 1.0 | 5318 | 0.6793 | 0.7855 |
0.6672 | 2.0 | 10636 | 0.6424 | 0.7946 |
0.6482 | 3.0 | 15954 | 0.6256 | 0.7988 |
0.6359 | 4.0 | 21272 | 0.6159 | 0.8013 |
0.628 | 5.0 | 26590 | 0.6094 | 0.8028 |
0.6226 | 6.0 | 31908 | 0.6052 | 0.8039 |
0.6186 | 7.0 | 37226 | 0.6021 | 0.8046 |
0.6158 | 8.0 | 42544 | 0.5998 | 0.8052 |
0.6139 | 9.0 | 47862 | 0.5984 | 0.8056 |
0.613 | 10.0 | 53180 | 0.5978 | 0.8057 |
Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.1.1+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
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