| --- |
| library_name: transformers |
| language: |
| - en |
| base_model: Hartunka/tiny_bert_km_10_v1 |
| tags: |
| - generated_from_trainer |
| datasets: |
| - glue |
| metrics: |
| - accuracy |
| - f1 |
| model-index: |
| - name: tiny_bert_km_10_v1_mrpc |
| results: |
| - task: |
| name: Text Classification |
| type: text-classification |
| dataset: |
| name: GLUE MRPC |
| type: glue |
| args: mrpc |
| metrics: |
| - name: Accuracy |
| type: accuracy |
| value: 0.7009803921568627 |
| - name: F1 |
| type: f1 |
| value: 0.8032258064516129 |
| --- |
| |
| <!-- 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_10_v1_mrpc |
| |
| This model is a fine-tuned version of [Hartunka/tiny_bert_km_10_v1](https://huggingface.co/Hartunka/tiny_bert_km_10_v1) on the GLUE MRPC dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.5893 |
| - Accuracy: 0.7010 |
| - F1: 0.8032 |
| - Combined Score: 0.7521 |
| |
| ## 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 | Accuracy | F1 | Combined Score | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------------:| |
| | 0.6324 | 1.0 | 15 | 0.6063 | 0.7108 | 0.8223 | 0.7665 | |
| | 0.596 | 2.0 | 30 | 0.5934 | 0.7034 | 0.8191 | 0.7613 | |
| | 0.5663 | 3.0 | 45 | 0.5923 | 0.7083 | 0.8200 | 0.7642 | |
| | 0.5449 | 4.0 | 60 | 0.5893 | 0.7010 | 0.8032 | 0.7521 | |
| | 0.4957 | 5.0 | 75 | 0.6304 | 0.6569 | 0.75 | 0.7034 | |
| | 0.4356 | 6.0 | 90 | 0.6516 | 0.6936 | 0.7871 | 0.7403 | |
| | 0.3509 | 7.0 | 105 | 0.7439 | 0.6887 | 0.7908 | 0.7397 | |
| | 0.2548 | 8.0 | 120 | 0.8600 | 0.6618 | 0.7553 | 0.7085 | |
| | 0.1693 | 9.0 | 135 | 1.0956 | 0.6225 | 0.7148 | 0.6687 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.50.2 |
| - Pytorch 2.2.1+cu121 |
| - Datasets 2.18.0 |
| - Tokenizers 0.21.1 |
| |
