| | --- |
| | library_name: transformers |
| | language: |
| | - en |
| | base_model: Hartunka/bert_base_km_50_v2 |
| | tags: |
| | - generated_from_trainer |
| | datasets: |
| | - glue |
| | metrics: |
| | - spearmanr |
| | model-index: |
| | - name: bert_base_km_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: 0.2528909067613722 |
| | --- |
| | |
| | <!-- 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_50_v2_stsb |
| | |
| | This model is a fine-tuned version of [Hartunka/bert_base_km_50_v2](https://huggingface.co/Hartunka/bert_base_km_50_v2) on the GLUE STSB dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 2.2956 |
| | - Pearson: 0.2660 |
| | - Spearmanr: 0.2529 |
| | - Combined Score: 0.2595 |
| | |
| | ## 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 | |
| | |:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:| |
| | | 2.863 | 1.0 | 23 | 2.9546 | 0.1062 | 0.1142 | 0.1102 | |
| | | 1.9987 | 2.0 | 46 | 2.3012 | 0.2302 | 0.2091 | 0.2197 | |
| | | 1.7872 | 3.0 | 69 | 2.2956 | 0.2660 | 0.2529 | 0.2595 | |
| | | 1.5246 | 4.0 | 92 | 2.4771 | 0.2736 | 0.2569 | 0.2652 | |
| | | 1.247 | 5.0 | 115 | 2.5712 | 0.2505 | 0.2352 | 0.2428 | |
| | | 0.9895 | 6.0 | 138 | 2.4369 | 0.3222 | 0.3227 | 0.3225 | |
| | | 0.77 | 7.0 | 161 | 2.3281 | 0.3366 | 0.3382 | 0.3374 | |
| | | 0.6098 | 8.0 | 184 | 2.4814 | 0.3255 | 0.3204 | 0.3230 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.50.2 |
| | - Pytorch 2.2.1+cu121 |
| | - Datasets 2.18.0 |
| | - Tokenizers 0.21.1 |
| | |
