| --- |
| language: |
| - en |
| base_model: Hartunka/tiny_bert_km_100_v1 |
| tags: |
| - generated_from_trainer |
| datasets: |
| - glue |
| metrics: |
| - spearmanr |
| model-index: |
| - name: tiny_bert_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: 0.17557479397825773 |
| --- |
| |
| <!-- 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_km_100_v1_stsb |
| |
| This model is a fine-tuned version of [Hartunka/tiny_bert_km_100_v1](https://huggingface.co/Hartunka/tiny_bert_km_100_v1) on the GLUE STSB dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 2.2017 |
| - Pearson: 0.1983 |
| - Spearmanr: 0.1756 |
| - Combined Score: 0.1870 |
| |
| ## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 50 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Pearson | Spearmanr | Combined Score | |
| |:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:| |
| | 3.7897 | 1.0 | 23 | 2.2017 | 0.1983 | 0.1756 | 0.1870 | |
| | 2.1293 | 2.0 | 46 | 2.2599 | 0.2062 | 0.1845 | 0.1953 | |
| | 1.9869 | 3.0 | 69 | 2.3074 | 0.1839 | 0.1590 | 0.1715 | |
| | 1.8494 | 4.0 | 92 | 2.3755 | 0.2103 | 0.1966 | 0.2034 | |
| | 1.62 | 5.0 | 115 | 2.3458 | 0.2589 | 0.2531 | 0.2560 | |
| | 1.4033 | 6.0 | 138 | 2.3234 | 0.2691 | 0.2705 | 0.2698 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.40.0 |
| - Pytorch 2.6.0+cu124 |
| - Datasets 3.5.0 |
| - Tokenizers 0.19.1 |
| |
