| | --- |
| | library_name: transformers |
| | language: |
| | - en |
| | base_model: Hartunka/tiny_bert_rand_5_v2 |
| | tags: |
| | - generated_from_trainer |
| | datasets: |
| | - glue |
| | metrics: |
| | - accuracy |
| | - f1 |
| | model-index: |
| | - name: tiny_bert_rand_5_v2_qqp |
| | results: |
| | - task: |
| | name: Text Classification |
| | type: text-classification |
| | dataset: |
| | name: GLUE QQP |
| | type: glue |
| | args: qqp |
| | metrics: |
| | - name: Accuracy |
| | type: accuracy |
| | value: 0.8146178580262181 |
| | - name: F1 |
| | type: f1 |
| | value: 0.7371558828686656 |
| | --- |
| | |
| | <!-- 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_rand_5_v2_qqp |
| | |
| | This model is a fine-tuned version of [Hartunka/tiny_bert_rand_5_v2](https://huggingface.co/Hartunka/tiny_bert_rand_5_v2) on the GLUE QQP dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.4161 |
| | - Accuracy: 0.8146 |
| | - F1: 0.7372 |
| | - Combined Score: 0.7759 |
| | |
| | ## 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 | |
| | |:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:--------------:| |
| | | 0.4948 | 1.0 | 1422 | 0.4481 | 0.7835 | 0.6860 | 0.7347 | |
| | | 0.4052 | 2.0 | 2844 | 0.4211 | 0.8023 | 0.7129 | 0.7576 | |
| | | 0.3464 | 3.0 | 4266 | 0.4161 | 0.8146 | 0.7372 | 0.7759 | |
| | | 0.2996 | 4.0 | 5688 | 0.4293 | 0.8191 | 0.7423 | 0.7807 | |
| | | 0.2623 | 5.0 | 7110 | 0.4363 | 0.8210 | 0.7572 | 0.7891 | |
| | | 0.2317 | 6.0 | 8532 | 0.4542 | 0.8218 | 0.7602 | 0.7910 | |
| | | 0.207 | 7.0 | 9954 | 0.4872 | 0.8216 | 0.7650 | 0.7933 | |
| | | 0.184 | 8.0 | 11376 | 0.5373 | 0.8273 | 0.7644 | 0.7959 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.50.2 |
| | - Pytorch 2.2.1+cu121 |
| | - Datasets 2.18.0 |
| | - Tokenizers 0.21.1 |
| | |
