| | --- |
| | library_name: transformers |
| | language: |
| | - en |
| | base_model: Hartunka/bert_base_rand_10_v2 |
| | tags: |
| | - generated_from_trainer |
| | datasets: |
| | - glue |
| | metrics: |
| | - spearmanr |
| | model-index: |
| | - name: bert_base_rand_10_v2_stsb |
| | results: |
| | - task: |
| | name: Text Classification |
| | type: text-classification |
| | dataset: |
| | name: GLUE STSB |
| | type: glue |
| | args: stsb |
| | metrics: |
| | - name: Spearmanr |
| | type: spearmanr |
| | value: 0.27121376913207584 |
| | --- |
| | |
| | <!-- 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_rand_10_v2_stsb |
| | |
| | This model is a fine-tuned version of [Hartunka/bert_base_rand_10_v2](https://huggingface.co/Hartunka/bert_base_rand_10_v2) on the GLUE STSB dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 2.3000 |
| | - Pearson: 0.2717 |
| | - Spearmanr: 0.2712 |
| | - Combined Score: 0.2714 |
| | |
| | ## 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 | |
| | |:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:| |
| | | 2.6698 | 1.0 | 23 | 2.3702 | 0.1154 | 0.0941 | 0.1048 | |
| | | 1.9073 | 2.0 | 46 | 2.5553 | 0.1762 | 0.1591 | 0.1676 | |
| | | 1.7118 | 3.0 | 69 | 2.5235 | 0.1830 | 0.1931 | 0.1880 | |
| | | 1.3839 | 4.0 | 92 | 2.3000 | 0.2717 | 0.2712 | 0.2714 | |
| | | 1.0676 | 5.0 | 115 | 2.6445 | 0.2323 | 0.2322 | 0.2322 | |
| | | 0.8664 | 6.0 | 138 | 2.7314 | 0.2522 | 0.2583 | 0.2552 | |
| | | 0.6989 | 7.0 | 161 | 2.6691 | 0.2727 | 0.2750 | 0.2738 | |
| | | 0.568 | 8.0 | 184 | 2.8615 | 0.2635 | 0.2681 | 0.2658 | |
| | | 0.4705 | 9.0 | 207 | 2.7113 | 0.2554 | 0.2386 | 0.2470 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.50.2 |
| | - Pytorch 2.2.1+cu121 |
| | - Datasets 2.18.0 |
| | - Tokenizers 0.21.1 |
| | |
