| | --- |
| | library_name: transformers |
| | language: |
| | - en |
| | base_model: Hartunka/bert_base_rand_50_v1 |
| | tags: |
| | - generated_from_trainer |
| | datasets: |
| | - glue |
| | metrics: |
| | - spearmanr |
| | model-index: |
| | - name: bert_base_rand_50_v1_stsb |
| | results: |
| | - task: |
| | name: Text Classification |
| | type: text-classification |
| | dataset: |
| | name: GLUE STSB |
| | type: glue |
| | args: stsb |
| | metrics: |
| | - name: Spearmanr |
| | type: spearmanr |
| | value: 0.25999577762490267 |
| | --- |
| | |
| | <!-- 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_50_v1_stsb |
| | |
| | This model is a fine-tuned version of [Hartunka/bert_base_rand_50_v1](https://huggingface.co/Hartunka/bert_base_rand_50_v1) on the GLUE STSB dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 2.2715 |
| | - Pearson: 0.2635 |
| | - Spearmanr: 0.2600 |
| | - Combined Score: 0.2618 |
| | |
| | ## 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 | |
| | |:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:| |
| | | 3.0174 | 1.0 | 23 | 2.9030 | 0.0773 | 0.0674 | 0.0724 | |
| | | 2.0319 | 2.0 | 46 | 2.4340 | 0.1690 | 0.1495 | 0.1593 | |
| | | 1.7905 | 3.0 | 69 | 2.3889 | 0.2034 | 0.1918 | 0.1976 | |
| | | 1.467 | 4.0 | 92 | 2.2715 | 0.2635 | 0.2600 | 0.2618 | |
| | | 1.1681 | 5.0 | 115 | 2.4279 | 0.2436 | 0.2402 | 0.2419 | |
| | | 1.0229 | 6.0 | 138 | 2.8679 | 0.2669 | 0.2723 | 0.2696 | |
| | | 0.7645 | 7.0 | 161 | 2.5480 | 0.2725 | 0.2734 | 0.2730 | |
| | | 0.6161 | 8.0 | 184 | 2.8213 | 0.2753 | 0.2854 | 0.2804 | |
| | | 0.4918 | 9.0 | 207 | 2.5409 | 0.2620 | 0.2639 | 0.2630 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.50.2 |
| | - Pytorch 2.2.1+cu121 |
| | - Datasets 2.18.0 |
| | - Tokenizers 0.21.1 |
| | |
