| base_model: readerbench/RoBERT-base | |
| tags: | |
| - generated_from_trainer | |
| metrics: | |
| - accuracy | |
| - precision | |
| - recall | |
| - f1 | |
| model-index: | |
| - name: ro-sentiment-02 | |
| 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-02 | |
| 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: 0.4093 | |
| - Accuracy: 0.8312 | |
| - Precision: 0.8488 | |
| - Recall: 0.8866 | |
| - F1: 0.8673 | |
| - F1 Weighted: 0.8298 | |
| ## 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: 6.3e-05 | |
| - train_batch_size: 96 | |
| - eval_batch_size: 192 | |
| - seed: 42 | |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 | |
| - lr_scheduler_type: linear | |
| - lr_scheduler_warmup_ratio: 0.25 | |
| - num_epochs: 10 | |
| ### Training results | |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | F1 Weighted | | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:-----------:| | |
| | 0.4289 | 1.0 | 1086 | 0.4168 | 0.8303 | 0.8868 | 0.8570 | 0.8717 | 0.8317 | | |
| | 0.3807 | 2.0 | 2172 | 0.3926 | 0.8424 | 0.8933 | 0.8680 | 0.8804 | 0.8434 | | |
| | 0.3306 | 3.0 | 3258 | 0.4093 | 0.8312 | 0.8488 | 0.8866 | 0.8673 | 0.8298 | | |
| ### Framework versions | |
| - Transformers 4.31.0 | |
| - Pytorch 2.0.1+cu118 | |
| - Datasets 2.14.3 | |
| - Tokenizers 0.13.3 | |