| license: mit | |
| tags: | |
| - generated_from_trainer | |
| metrics: | |
| - accuracy | |
| - precision | |
| - recall | |
| - f1 | |
| model-index: | |
| - name: IQA_classification | |
| 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. --> | |
| # IQA_classification | |
| This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset. | |
| It achieves the following results on the evaluation set: | |
| - Loss: 1.0718 | |
| - Accuracy: 0.4862 | |
| - Precision: 0.3398 | |
| - Recall: 0.4862 | |
| - F1: 0.3270 | |
| ## 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: 2 | |
| ### Training results | |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| | |
| | 1.3973 | 1.0 | 28 | 1.1588 | 0.4771 | 0.2276 | 0.4771 | 0.3082 | | |
| | 1.1575 | 2.0 | 56 | 1.0718 | 0.4862 | 0.3398 | 0.4862 | 0.3270 | | |
| ### Framework versions | |
| - Transformers 4.18.0 | |
| - Pytorch 1.11.0+cu113 | |
| - Datasets 2.1.0 | |
| - Tokenizers 0.12.1 | |