<!-- 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. -->
SA-roberta-e3-w1-1.5-b16-mt4-w0.01
This model is a fine-tuned version of Amalq/autotrain-smm4h_large_roberta_clean-874027878 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2790
- Accuracy: 0.94
- F1: 0.9470
- Precision: 0.9437
- Recall: 0.9504
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: 3
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
---|---|---|---|---|---|---|---|
No log | 1.0 | 285 | 0.2093 | 0.915 | 0.9214 | 0.9632 | 0.8830 |
0.259 | 2.0 | 570 | 0.2161 | 0.935 | 0.9418 | 0.9512 | 0.9326 |
0.259 | 3.0 | 855 | 0.2790 | 0.94 | 0.9470 | 0.9437 | 0.9504 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3