| | --- |
| | library_name: transformers |
| | language: |
| | - en |
| | base_model: Hartunka/bert_base_rand_10_v1 |
| | tags: |
| | - generated_from_trainer |
| | datasets: |
| | - glue |
| | metrics: |
| | - spearmanr |
| | model-index: |
| | - name: bert_base_rand_10_v1_stsb |
| | results: |
| | - task: |
| | name: Text Classification |
| | type: text-classification |
| | dataset: |
| | name: GLUE STSB |
| | type: glue |
| | args: stsb |
| | metrics: |
| | - name: Spearmanr |
| | type: spearmanr |
| | value: 0.2237898877305157 |
| | --- |
| | |
| | <!-- 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_v1_stsb |
| | |
| | This model is a fine-tuned version of [Hartunka/bert_base_rand_10_v1](https://huggingface.co/Hartunka/bert_base_rand_10_v1) on the GLUE STSB dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 2.3422 |
| | - Pearson: 0.2300 |
| | - Spearmanr: 0.2238 |
| | - Combined Score: 0.2269 |
| | |
| | ## 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 | |
| | |:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:| |
| | | 2.5501 | 1.0 | 23 | 2.5206 | 0.1247 | 0.1086 | 0.1166 | |
| | | 1.9123 | 2.0 | 46 | 2.3921 | 0.1624 | 0.1434 | 0.1529 | |
| | | 1.6606 | 3.0 | 69 | 2.3422 | 0.2300 | 0.2238 | 0.2269 | |
| | | 1.2907 | 4.0 | 92 | 2.5930 | 0.2617 | 0.2667 | 0.2642 | |
| | | 0.9783 | 5.0 | 115 | 2.4709 | 0.2854 | 0.2803 | 0.2828 | |
| | | 0.7673 | 6.0 | 138 | 2.4687 | 0.3073 | 0.3021 | 0.3047 | |
| | | 0.5922 | 7.0 | 161 | 2.4917 | 0.3069 | 0.3033 | 0.3051 | |
| | | 0.4832 | 8.0 | 184 | 2.7527 | 0.2931 | 0.2892 | 0.2911 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.50.2 |
| | - Pytorch 2.2.1+cu121 |
| | - Datasets 2.18.0 |
| | - Tokenizers 0.21.1 |
| | |
