| | --- |
| | library_name: transformers |
| | language: |
| | - en |
| | base_model: Hartunka/distilbert_rand_100_v2 |
| | tags: |
| | - generated_from_trainer |
| | datasets: |
| | - glue |
| | metrics: |
| | - matthews_correlation |
| | - accuracy |
| | model-index: |
| | - name: distilbert_rand_100_v2_cola |
| | results: |
| | - task: |
| | name: Text Classification |
| | type: text-classification |
| | dataset: |
| | name: GLUE COLA |
| | type: glue |
| | args: cola |
| | metrics: |
| | - name: Matthews Correlation |
| | type: matthews_correlation |
| | value: 0.07482349006947582 |
| | - name: Accuracy |
| | type: accuracy |
| | value: 0.6826462149620056 |
| | --- |
| | |
| | <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| | should probably proofread and complete it, then remove this comment. --> |
| |
|
| | # distilbert_rand_100_v2_cola |
| |
|
| | This model is a fine-tuned version of [Hartunka/distilbert_rand_100_v2](https://huggingface.co/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 |
| |
|
