metadata
library_name: transformers
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: model
results: []
model
This model is a fine-tuned version of roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3309
- Precision: 0.6214
- Recall: 0.5332
- F1: 0.5410
- Accuracy: 0.9060
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.1159 | 0.8547 | 100 | 0.3248 | 0.6055 | 0.5785 | 0.5888 | 0.8852 |
| 0.202 | 1.7094 | 200 | 0.3075 | 0.6661 | 0.5444 | 0.5581 | 0.9087 |
| 0.1593 | 2.5641 | 300 | 0.3221 | 0.6624 | 0.5473 | 0.5622 | 0.9079 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.20.3