| | --- |
| | library_name: transformers |
| | language: |
| | - en |
| | base_model: Hartunka/bert_base_km_5_v2 |
| | tags: |
| | - generated_from_trainer |
| | datasets: |
| | - glue |
| | metrics: |
| | - spearmanr |
| | model-index: |
| | - name: bert_base_km_5_v2_stsb |
| | results: |
| | - task: |
| | name: Text Classification |
| | type: text-classification |
| | dataset: |
| | name: GLUE STSB |
| | type: glue |
| | args: stsb |
| | metrics: |
| | - name: Spearmanr |
| | type: spearmanr |
| | value: 0.4647300879795164 |
| | --- |
| | |
| | <!-- 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. --> |
| |
|
| | # bert_base_km_5_v2_stsb |
| | |
| | This model is a fine-tuned version of [Hartunka/bert_base_km_5_v2](https://huggingface.co/Hartunka/bert_base_km_5_v2) on the GLUE STSB dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 1.8177 |
| | - Pearson: 0.4729 |
| | - Spearmanr: 0.4647 |
| | - Combined Score: 0.4688 |
| | |
| | ## 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 | |
| | |:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:| |
| | | 2.6459 | 1.0 | 23 | 2.4966 | 0.1835 | 0.1715 | 0.1775 | |
| | | 1.8235 | 2.0 | 46 | 2.2914 | 0.3594 | 0.3550 | 0.3572 | |
| | | 1.4306 | 3.0 | 69 | 2.0514 | 0.4242 | 0.4267 | 0.4254 | |
| | | 1.0154 | 4.0 | 92 | 1.8177 | 0.4729 | 0.4647 | 0.4688 | |
| | | 0.6595 | 5.0 | 115 | 2.1356 | 0.4311 | 0.4288 | 0.4299 | |
| | | 0.5214 | 6.0 | 138 | 2.0065 | 0.4628 | 0.4615 | 0.4621 | |
| | | 0.3787 | 7.0 | 161 | 2.2221 | 0.4495 | 0.4408 | 0.4451 | |
| | | 0.3169 | 8.0 | 184 | 2.1129 | 0.4652 | 0.4569 | 0.4611 | |
| | | 0.2679 | 9.0 | 207 | 2.1071 | 0.4559 | 0.4422 | 0.4491 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.50.2 |
| | - Pytorch 2.2.1+cu121 |
| | - Datasets 2.18.0 |
| | - Tokenizers 0.21.1 |
| | |
