metadata
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
base_model: roberta-large
model-index:
- name: dcai2023-roberta
results: []
dcai2023-roberta
This model is a fine-tuned version of roberta-large on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.7027
- Accuracy: 0.7383
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: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.9281 | 1.0 | 530 | 0.7301 | 0.7136 |
| 0.6474 | 2.0 | 1060 | 0.7027 | 0.7383 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.0.post200
- Datasets 2.9.0
- Tokenizers 0.13.2