metadata
library_name: transformers
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: cf-robert-finetuned1
results: []
cf-robert-finetuned1
This model is a fine-tuned version of roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4047
- F1: 0.4907
- Roc Auc: 0.6667
- Accuracy: 0.2115
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 | F1 | Roc Auc | Accuracy |
|---|---|---|---|---|---|---|
| 0.4485 | 1.0 | 908 | 0.4480 | 0.2852 | 0.5789 | 0.1112 |
| 0.4367 | 2.0 | 1816 | 0.4108 | 0.4742 | 0.6597 | 0.2037 |
| 0.3944 | 3.0 | 2724 | 0.4009 | 0.4916 | 0.6681 | 0.2225 |
Framework versions
- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3