distilbert_rand_100_v2_cola
This model is a fine-tuned version of Hartunka/distilbert_rand_100_v2 on the GLUE COLA dataset. It achieves the following results on the evaluation set:
- Loss: 0.6132
- Matthews Correlation: 0.0748
- Accuracy: 0.6826
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: 256
- eval_batch_size: 256
- seed: 10
- 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
- num_epochs: 50
Training results
| Training Loss | Epoch | Step | Validation Loss | Matthews Correlation | Accuracy |
|---|---|---|---|---|---|
| 0.6127 | 1.0 | 34 | 0.6148 | 0.0 | 0.6913 |
| 0.591 | 2.0 | 68 | 0.6217 | -0.0163 | 0.6884 |
| 0.5421 | 3.0 | 102 | 0.6132 | 0.0748 | 0.6826 |
| 0.4864 | 4.0 | 136 | 0.7308 | 0.1075 | 0.6596 |
| 0.4232 | 5.0 | 170 | 0.7523 | 0.1393 | 0.6577 |
| 0.3623 | 6.0 | 204 | 0.8275 | 0.1102 | 0.6500 |
| 0.3196 | 7.0 | 238 | 0.9465 | 0.1025 | 0.6328 |
| 0.2848 | 8.0 | 272 | 1.0343 | 0.1314 | 0.6481 |
Framework versions
- Transformers 4.50.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.21.1
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Model tree for Hartunka/distilbert_rand_100_v2_cola
Base model
Hartunka/distilbert_rand_100_v2Dataset used to train Hartunka/distilbert_rand_100_v2_cola
Evaluation results
- Matthews Correlation on GLUE COLAself-reported0.075
- Accuracy on GLUE COLAself-reported0.683