| language: | |
| - en | |
| license: apache-2.0 | |
| tags: | |
| - generated_from_trainer | |
| datasets: | |
| - glue | |
| metrics: | |
| - spearmanr | |
| base_model: bert-base-uncased | |
| model-index: | |
| - name: bert-base-uncased-stsb | |
| results: | |
| - task: | |
| type: text-classification | |
| name: Text Classification | |
| dataset: | |
| name: GLUE STSB | |
| type: glue | |
| args: stsb | |
| metrics: | |
| - type: spearmanr | |
| value: 0.8843169724798454 | |
| name: Spearmanr | |
| <!-- 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-uncased-stsb | |
| This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the GLUE STSB dataset. | |
| It achieves the following results on the evaluation set: | |
| - Loss: 0.5144 | |
| - Pearson: 0.8875 | |
| - Spearmanr: 0.8843 | |
| - Combined Score: 0.8859 | |
| ## 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: 2e-05 | |
| - train_batch_size: 32 | |
| - eval_batch_size: 8 | |
| - seed: 42 | |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 | |
| - lr_scheduler_type: linear | |
| - num_epochs: 3.0 | |
| ### Training results | |
| | Training Loss | Epoch | Step | Validation Loss | Pearson | Spearmanr | Combined Score | | |
| |:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:| | |
| | No log | 1.0 | 180 | 0.5179 | 0.8806 | 0.8735 | 0.8771 | | |
| | No log | 2.0 | 360 | 0.5145 | 0.8850 | 0.8820 | 0.8835 | | |
| | 0.7868 | 3.0 | 540 | 0.5144 | 0.8875 | 0.8843 | 0.8859 | | |
| ### Framework versions | |
| - Transformers 4.20.0.dev0 | |
| - Pytorch 1.11.0+cu113 | |
| - Datasets 2.1.0 | |
| - Tokenizers 0.12.1 | |