| | --- |
| | library_name: transformers |
| | language: |
| | - en |
| | base_model: Hartunka/tiny_bert_rand_100_v2 |
| | tags: |
| | - generated_from_trainer |
| | datasets: |
| | - glue |
| | metrics: |
| | - spearmanr |
| | model-index: |
| | - name: tiny_bert_rand_100_v2_stsb |
| | results: |
| | - task: |
| | name: Text Classification |
| | type: text-classification |
| | dataset: |
| | name: GLUE STSB |
| | type: glue |
| | args: stsb |
| | metrics: |
| | - name: Spearmanr |
| | type: spearmanr |
| | value: 0.17464416855612533 |
| | --- |
| | |
| | <!-- 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_rand_100_v2_stsb |
| | |
| | This model is a fine-tuned version of [Hartunka/tiny_bert_rand_100_v2](https://huggingface.co/Hartunka/tiny_bert_rand_100_v2) on the GLUE STSB dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 2.3571 |
| | - Pearson: 0.1904 |
| | - Spearmanr: 0.1746 |
| | - Combined Score: 0.1825 |
| | |
| | ## 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 | |
| | |:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:| |
| | | 3.0934 | 1.0 | 23 | 2.4179 | 0.1274 | 0.1252 | 0.1263 | |
| | | 2.0262 | 2.0 | 46 | 2.8227 | 0.0906 | 0.0700 | 0.0803 | |
| | | 1.8632 | 3.0 | 69 | 2.3571 | 0.1904 | 0.1746 | 0.1825 | |
| | | 1.6504 | 4.0 | 92 | 2.4674 | 0.2405 | 0.2359 | 0.2382 | |
| | | 1.376 | 5.0 | 115 | 2.4109 | 0.2443 | 0.2405 | 0.2424 | |
| | | 1.1686 | 6.0 | 138 | 2.5538 | 0.2573 | 0.2599 | 0.2586 | |
| | | 0.9782 | 7.0 | 161 | 2.6227 | 0.2622 | 0.2656 | 0.2639 | |
| | | 0.8135 | 8.0 | 184 | 3.0193 | 0.2305 | 0.2377 | 0.2341 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.50.2 |
| | - Pytorch 2.2.1+cu121 |
| | - Datasets 2.18.0 |
| | - Tokenizers 0.21.1 |
| | |
