| | --- |
| | library_name: transformers |
| | language: |
| | - en |
| | base_model: Hartunka/tiny_bert_rand_50_v2 |
| | tags: |
| | - generated_from_trainer |
| | datasets: |
| | - glue |
| | metrics: |
| | - spearmanr |
| | model-index: |
| | - name: tiny_bert_rand_50_v2_stsb |
| | results: |
| | - task: |
| | name: Text Classification |
| | type: text-classification |
| | dataset: |
| | name: GLUE STSB |
| | type: glue |
| | args: stsb |
| | metrics: |
| | - name: Spearmanr |
| | type: spearmanr |
| | value: 0.25802571079319986 |
| | --- |
| | |
| | <!-- 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_50_v2_stsb |
| | |
| | This model is a fine-tuned version of [Hartunka/tiny_bert_rand_50_v2](https://huggingface.co/Hartunka/tiny_bert_rand_50_v2) on the GLUE STSB dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 2.2828 |
| | - Pearson: 0.2634 |
| | - Spearmanr: 0.2580 |
| | - Combined Score: 0.2607 |
| | |
| | ## 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 | Pearson | Spearmanr | Combined Score | |
| | |:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:| |
| | | 3.577 | 1.0 | 23 | 2.3197 | 0.1206 | 0.1077 | 0.1142 | |
| | | 2.0557 | 2.0 | 46 | 2.4031 | 0.1291 | 0.1249 | 0.1270 | |
| | | 1.8854 | 3.0 | 69 | 2.3713 | 0.2039 | 0.1988 | 0.2013 | |
| | | 1.7118 | 4.0 | 92 | 2.3258 | 0.2474 | 0.2463 | 0.2469 | |
| | | 1.4486 | 5.0 | 115 | 2.2828 | 0.2634 | 0.2580 | 0.2607 | |
| | | 1.2898 | 6.0 | 138 | 2.7080 | 0.2622 | 0.2744 | 0.2683 | |
| | | 1.0578 | 7.0 | 161 | 2.6507 | 0.2815 | 0.2900 | 0.2857 | |
| | | 0.8953 | 8.0 | 184 | 2.8633 | 0.2585 | 0.2633 | 0.2609 | |
| | | 0.7584 | 9.0 | 207 | 3.1760 | 0.2421 | 0.2473 | 0.2447 | |
| | | 0.6589 | 10.0 | 230 | 3.0019 | 0.2613 | 0.2697 | 0.2655 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.50.2 |
| | - Pytorch 2.2.1+cu121 |
| | - Datasets 2.18.0 |
| | - Tokenizers 0.21.1 |
| | |
