--- library_name: transformers language: - en base_model: Hartunka/tiny_bert_rand_10_v1 tags: - generated_from_trainer datasets: - glue metrics: - matthews_correlation - accuracy model-index: - name: tiny_bert_rand_10_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: 0.03640174058932784 - name: Accuracy type: accuracy value: 0.6912751793861389 --- # tiny_bert_rand_10_v1_cola This model is a fine-tuned version of [Hartunka/tiny_bert_rand_10_v1](https://huggingface.co/Hartunka/tiny_bert_rand_10_v1) on the GLUE COLA dataset. It achieves the following results on the evaluation set: - Loss: 0.6126 - Matthews Correlation: 0.0364 - 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: 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 | |:-------------:|:-----:|:----:|:---------------:|:--------------------:|:--------:| | 0.6189 | 1.0 | 34 | 0.6156 | 0.0 | 0.6913 | | 0.6016 | 2.0 | 68 | 0.6129 | 0.0 | 0.6913 | | 0.5821 | 3.0 | 102 | 0.6126 | 0.0364 | 0.6913 | | 0.5453 | 4.0 | 136 | 0.6591 | 0.0868 | 0.6798 | | 0.4994 | 5.0 | 170 | 0.6550 | 0.1096 | 0.6702 | | 0.4658 | 6.0 | 204 | 0.7170 | 0.1018 | 0.6462 | | 0.4329 | 7.0 | 238 | 0.7630 | 0.0867 | 0.6290 | | 0.4002 | 8.0 | 272 | 0.8305 | 0.0734 | 0.6357 | ### Framework versions - Transformers 4.50.2 - Pytorch 2.2.1+cu121 - Datasets 2.18.0 - Tokenizers 0.21.1