| --- |
| language: |
| - en |
| base_model: Hartunka/tiny_bert_km_100_v1 |
| tags: |
| - generated_from_trainer |
| datasets: |
| - glue |
| metrics: |
| - matthews_correlation |
| - accuracy |
| model-index: |
| - name: tiny_bert_km_100_v1_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: 0.0 |
| - name: Accuracy |
| type: accuracy |
| value: 0.6912751793861389 |
| --- |
| |
| <!-- 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. --> |
|
|
| # tiny_bert_km_100_v1_cola |
| |
| This model is a fine-tuned version of [Hartunka/tiny_bert_km_100_v1](https://huggingface.co/Hartunka/tiny_bert_km_100_v1) on the GLUE COLA dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.6238 |
| - Matthews Correlation: 0.0 |
| - Accuracy: 0.6913 |
| |
| ## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 50 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Matthews Correlation | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:--------------------:|:--------:| |
| | 0.6196 | 1.0 | 34 | 0.6238 | 0.0 | 0.6913 | |
| | 0.6075 | 2.0 | 68 | 0.6263 | 0.0 | 0.6913 | |
| | 0.5972 | 3.0 | 102 | 0.6293 | 0.0 | 0.6913 | |
| | 0.5804 | 4.0 | 136 | 0.6354 | -0.0196 | 0.6683 | |
| | 0.5561 | 5.0 | 170 | 0.6381 | 0.0361 | 0.6673 | |
| | 0.5088 | 6.0 | 204 | 0.6593 | 0.0537 | 0.6616 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.40.0 |
| - Pytorch 2.6.0+cu124 |
| - Datasets 3.5.0 |
| - Tokenizers 0.19.1 |
| |
