| license: agpl-3.0 | |
| tags: | |
| - generated_from_trainer | |
| datasets: | |
| - glue | |
| metrics: | |
| - spearmanr | |
| pipeline_tag: sentence-similarity | |
| base_model: vesteinn/XLMR-ENIS | |
| model-index: | |
| - name: XLMR-ENIS-finetuned-stsb | |
| results: | |
| - task: | |
| type: text-classification | |
| name: Text Classification | |
| dataset: | |
| name: glue | |
| type: glue | |
| args: stsb | |
| metrics: | |
| - type: spearmanr | |
| value: 0.8887885342806044 | |
| 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. --> | |
| # XLMR-ENIS-finetuned-stsb | |
| This model is a fine-tuned version of [vesteinn/XLMR-ENIS](https://huggingface.co/vesteinn/XLMR-ENIS) on the glue dataset. | |
| It achieves the following results on the evaluation set: | |
| - Loss: 0.5232 | |
| - Pearson: 0.8915 | |
| - Spearmanr: 0.8888 | |
| ## 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: 16 | |
| - eval_batch_size: 16 | |
| - seed: 42 | |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 | |
| - lr_scheduler_type: linear | |
| - num_epochs: 5 | |
| ### Training results | |
| | Training Loss | Epoch | Step | Validation Loss | Pearson | Spearmanr | | |
| |:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:| | |
| | No log | 1.0 | 360 | 0.6330 | 0.8562 | 0.8570 | | |
| | 1.2835 | 2.0 | 720 | 0.6368 | 0.8790 | 0.8781 | | |
| | 0.4518 | 3.0 | 1080 | 0.5352 | 0.8883 | 0.8852 | | |
| | 0.4518 | 4.0 | 1440 | 0.4881 | 0.8910 | 0.8885 | | |
| | 0.288 | 5.0 | 1800 | 0.5232 | 0.8915 | 0.8888 | | |
| ### Framework versions | |
| - Transformers 4.11.3 | |
| - Pytorch 1.9.0+cu111 | |
| - Datasets 1.13.0 | |
| - Tokenizers 0.10.3 | |