| | --- |
| | library_name: transformers |
| | language: |
| | - en |
| | base_model: Hartunka/distilbert_km_5_v2 |
| | tags: |
| | - generated_from_trainer |
| | datasets: |
| | - glue |
| | metrics: |
| | - spearmanr |
| | model-index: |
| | - name: distilbert_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: 0.42646563812642424 |
| | --- |
| | |
| | <!-- 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. --> |
| |
|
| | # distilbert_km_5_v2_stsb |
| |
|
| | This model is a fine-tuned version of [Hartunka/distilbert_km_5_v2](https://huggingface.co/Hartunka/distilbert_km_5_v2) on the GLUE STSB dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 1.9509 |
| | - Pearson: 0.4293 |
| | - Spearmanr: 0.4265 |
| | - Combined Score: 0.4279 |
| |
|
| | ## 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 | |
| | |:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:| |
| | | 2.855 | 1.0 | 23 | 2.3396 | 0.1598 | 0.1539 | 0.1568 | |
| | | 1.8792 | 2.0 | 46 | 2.2082 | 0.2599 | 0.2485 | 0.2542 | |
| | | 1.531 | 3.0 | 69 | 2.1020 | 0.3665 | 0.3604 | 0.3634 | |
| | | 1.1221 | 4.0 | 92 | 1.9509 | 0.4293 | 0.4265 | 0.4279 | |
| | | 0.7863 | 5.0 | 115 | 2.1921 | 0.4221 | 0.4242 | 0.4231 | |
| | | 0.5364 | 6.0 | 138 | 2.1038 | 0.4496 | 0.4501 | 0.4498 | |
| | | 0.4273 | 7.0 | 161 | 2.0297 | 0.4535 | 0.4503 | 0.4519 | |
| | | 0.3516 | 8.0 | 184 | 2.1971 | 0.4279 | 0.4217 | 0.4248 | |
| | | 0.2901 | 9.0 | 207 | 2.0682 | 0.4296 | 0.4233 | 0.4265 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.50.2 |
| | - Pytorch 2.2.1+cu121 |
| | - Datasets 2.18.0 |
| | - Tokenizers 0.21.1 |
| |
|
