| base_model: readerbench/RoBERT-base | |
| tags: | |
| - generated_from_trainer | |
| metrics: | |
| - accuracy | |
| - precision | |
| - recall | |
| - f1 | |
| model-index: | |
| - name: ro-sentiment-03 | |
| 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. --> | |
| # ro-sentiment-03 | |
| This model is a fine-tuned version of [readerbench/RoBERT-base](https://huggingface.co/readerbench/RoBERT-base) on the None dataset. | |
| It achieves the following results on the evaluation set: | |
| - Loss: 0.3923 | |
| - Accuracy: 0.8307 | |
| - Precision: 0.8366 | |
| - Recall: 0.8959 | |
| - F1: 0.8652 | |
| - F1 Weighted: 0.8287 | |
| ## 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: 6e-05 | |
| - train_batch_size: 64 | |
| - eval_batch_size: 128 | |
| - seed: 42 | |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 | |
| - lr_scheduler_type: linear | |
| - lr_scheduler_warmup_ratio: 0.2 | |
| - num_epochs: 10 | |
| ### Training results | |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | F1 Weighted | | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:-----------:| | |
| | 0.4198 | 1.0 | 1629 | 0.3983 | 0.8377 | 0.8791 | 0.8721 | 0.8756 | 0.8380 | | |
| | 0.3861 | 2.0 | 3258 | 0.4312 | 0.8429 | 0.8963 | 0.8665 | 0.8812 | 0.8442 | | |
| | 0.3189 | 3.0 | 4887 | 0.3923 | 0.8307 | 0.8366 | 0.8959 | 0.8652 | 0.8287 | | |
| ### Framework versions | |
| - Transformers 4.31.0 | |
| - Pytorch 2.0.1+cu118 | |
| - Datasets 2.14.3 | |
| - Tokenizers 0.13.3 | |