| --- |
| tags: |
| - generated_from_trainer |
| datasets: |
| - glue |
| metrics: |
| - accuracy |
| model_index: |
| - name: hackMIT-finetuned-sst2 |
| results: |
| - task: |
| name: Text Classification |
| type: text-classification |
| dataset: |
| name: glue |
| type: glue |
| args: sst2 |
| metric: |
| name: Accuracy |
| type: accuracy |
| value: 0.7970183486238532 |
| --- |
| |
| <!-- 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. --> |
|
|
| # hackMIT-finetuned-sst2 |
|
|
| This model is a fine-tuned version of [Blaine-Mason/hackMIT-finetuned-sst2](https://huggingface.co/Blaine-Mason/hackMIT-finetuned-sst2) on the glue dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 1.0046 |
| - Accuracy: 0.7970 |
|
|
| ## 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: 1.7339491016138283e-05 |
| - train_batch_size: 64 |
| - eval_batch_size: 16 |
| - seed: 23 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 3 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | 0.0652 | 1.0 | 1053 | 0.9837 | 0.7970 | |
| | 0.0586 | 2.0 | 2106 | 0.9927 | 0.7959 | |
| | 0.0549 | 3.0 | 3159 | 1.0046 | 0.7970 | |
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|
| ### Framework versions |
|
|
| - Transformers 4.9.2 |
| - Pytorch 1.9.0+cu102 |
| - Datasets 1.11.0 |
| - Tokenizers 0.10.3 |
|
|
