| license: mit | |
| tags: | |
| - generated_from_trainer | |
| metrics: | |
| - accuracy | |
| model-index: | |
| - name: sentiment-model-saagie | |
| results: [] | |
| <!-- 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. --> | |
| # sentiment-model-saagie | |
| This model is a fine-tuned version of [prajjwal1/bert-tiny](https://huggingface.co/prajjwal1/bert-tiny) on the None dataset. | |
| It achieves the following results on the evaluation set: | |
| - Loss: 0.5475 | |
| - Accuracy: 0.7933 | |
| ## 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: 8 | |
| - 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 | |
| ### Training results | |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:| | |
| | 0.5168 | 1.0 | 1500 | 0.4738 | 0.7733 | | |
| | 0.3809 | 2.0 | 3000 | 0.5253 | 0.7917 | | |
| | 0.3372 | 3.0 | 4500 | 0.5475 | 0.7933 | | |
| ### Framework versions | |
| - Transformers 4.18.0 | |
| - Pytorch 1.8.1 | |
| - Datasets 2.12.0 | |
| - Tokenizers 0.12.1 | |