NeoBERT_druglib_regression_6ep_5e-06lr_0.03wd_0.2wr_rocauc_oversample_v1
This model is a fine-tuned version of chandar-lab/NeoBERT on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5216
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-06
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.2
- num_epochs: 6
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.7329 | 1.0 | 311 | 0.7037 |
| 0.412 | 2.0 | 622 | 0.5042 |
| 0.4259 | 3.0 | 933 | 0.5356 |
| 0.1746 | 4.0 | 1244 | 0.5006 |
| 0.1065 | 5.0 | 1555 | 0.5534 |
| 0.0631 | 6.0 | 1866 | 0.5086 |
Framework versions
- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.3.1
- Tokenizers 0.21.0
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Model tree for mlynatom/NeoBERT_druglib_regression_6ep_5e-06lr_0.03wd_0.2wr_rocauc_oversample_v1
Base model
chandar-lab/NeoBERT