| | --- |
| | library_name: transformers |
| | language: |
| | - en |
| | base_model: Hartunka/bert_base_km_100_v1 |
| | tags: |
| | - generated_from_trainer |
| | datasets: |
| | - glue |
| | metrics: |
| | - spearmanr |
| | model-index: |
| | - name: bert_base_km_100_v1_stsb |
| | results: |
| | - task: |
| | name: Text Classification |
| | type: text-classification |
| | dataset: |
| | name: GLUE STSB |
| | type: glue |
| | args: stsb |
| | metrics: |
| | - name: Spearmanr |
| | type: spearmanr |
| | value: 0.29833547420506246 |
| | --- |
| | |
| | <!-- 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_100_v1_stsb |
| | |
| | This model is a fine-tuned version of [Hartunka/bert_base_km_100_v1](https://huggingface.co/Hartunka/bert_base_km_100_v1) on the GLUE STSB dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 2.2490 |
| | - Pearson: 0.2995 |
| | - Spearmanr: 0.2983 |
| | - Combined Score: 0.2989 |
| | |
| | ## 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 | |
| | |:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:| |
| | | 2.7396 | 1.0 | 23 | 2.5547 | 0.1514 | 0.1351 | 0.1432 | |
| | | 1.9555 | 2.0 | 46 | 2.3166 | 0.1712 | 0.1497 | 0.1605 | |
| | | 1.749 | 3.0 | 69 | 2.3146 | 0.2127 | 0.2000 | 0.2064 | |
| | | 1.3865 | 4.0 | 92 | 2.2490 | 0.2995 | 0.2983 | 0.2989 | |
| | | 0.9821 | 5.0 | 115 | 2.7978 | 0.2457 | 0.2364 | 0.2410 | |
| | | 0.6935 | 6.0 | 138 | 2.8239 | 0.2598 | 0.2516 | 0.2557 | |
| | | 0.4947 | 7.0 | 161 | 2.9618 | 0.2405 | 0.2309 | 0.2357 | |
| | | 0.3874 | 8.0 | 184 | 2.7149 | 0.2566 | 0.2501 | 0.2533 | |
| | | 0.31 | 9.0 | 207 | 2.5269 | 0.2768 | 0.2706 | 0.2737 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.50.2 |
| | - Pytorch 2.2.1+cu121 |
| | - Datasets 2.18.0 |
| | - Tokenizers 0.21.1 |
| | |
