| | --- |
| | library_name: transformers |
| | language: |
| | - en |
| | base_model: Hartunka/bert_base_rand_100_v1 |
| | tags: |
| | - generated_from_trainer |
| | datasets: |
| | - glue |
| | metrics: |
| | - spearmanr |
| | model-index: |
| | - name: bert_base_rand_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: 0.1464988583508184 |
| | --- |
| | |
| | <!-- 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_100_v1_stsb |
| | |
| | This model is a fine-tuned version of [Hartunka/bert_base_rand_100_v1](https://huggingface.co/Hartunka/bert_base_rand_100_v1) on the GLUE STSB dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 2.2721 |
| | - Pearson: 0.1714 |
| | - Spearmanr: 0.1465 |
| | - Combined Score: 0.1590 |
| | |
| | ## 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 | |
| | |:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:| |
| | | 2.928 | 1.0 | 23 | 2.4646 | 0.0973 | 0.0902 | 0.0937 | |
| | | 1.9606 | 2.0 | 46 | 2.2721 | 0.1714 | 0.1465 | 0.1590 | |
| | | 1.6768 | 3.0 | 69 | 2.3989 | 0.2291 | 0.2257 | 0.2274 | |
| | | 1.3265 | 4.0 | 92 | 2.4733 | 0.2693 | 0.2725 | 0.2709 | |
| | | 1.0076 | 5.0 | 115 | 2.8602 | 0.2450 | 0.2457 | 0.2454 | |
| | | 0.7949 | 6.0 | 138 | 2.7485 | 0.2606 | 0.2643 | 0.2624 | |
| | | 0.626 | 7.0 | 161 | 2.5590 | 0.2792 | 0.2811 | 0.2801 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.50.2 |
| | - Pytorch 2.2.1+cu121 |
| | - Datasets 2.18.0 |
| | - Tokenizers 0.21.1 |
| | |
