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distilbert_add_GLUE_Experiment_logit_kd_pretrain_cola
This model is a fine-tuned version of gokuls/distilbert_add_pre-training-complete on the GLUE COLA dataset. It achieves the following results on the evaluation set:
- Loss: 0.6826
- Matthews Correlation: 0.0
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
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Matthews Correlation |
|---|---|---|---|---|
| 0.8045 | 1.0 | 34 | 0.6851 | 0.0 |
| 0.7928 | 2.0 | 68 | 0.6826 | 0.0 |
| 0.7843 | 3.0 | 102 | 0.6896 | 0.0 |
| 0.7612 | 4.0 | 136 | 0.7137 | -0.0293 |
| 0.7314 | 5.0 | 170 | 0.7249 | 0.0677 |
| 0.698 | 6.0 | 204 | 0.7111 | 0.0632 |
| 0.6717 | 7.0 | 238 | 0.7198 | 0.0829 |
Framework versions
- Transformers 4.26.0
- Pytorch 1.14.0a0+410ce96
- Datasets 2.9.0
- Tokenizers 0.13.2
