metadata
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: v9_checkpoints
results: []
v9_checkpoints
This model is a fine-tuned version of roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6931
- Accuracy: 0.4851
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: 5e-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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.6962 | 1.0 | 746 | 0.6931 | 0.5478 |
| 0.6971 | 2.0 | 1492 | 0.6931 | 0.5350 |
| 0.6958 | 3.0 | 2238 | 0.6931 | 0.5538 |
| 0.6951 | 4.0 | 2984 | 0.6931 | 0.5595 |
| 0.6953 | 5.0 | 3730 | 0.6931 | 0.5360 |
| 0.6959 | 6.0 | 4476 | 0.6931 | 0.4509 |
| 0.6957 | 7.0 | 5222 | 0.6931 | 0.5357 |
| 0.6939 | 8.0 | 5968 | 0.6931 | 0.5273 |
| 0.6946 | 9.0 | 6714 | 0.6931 | 0.4495 |
| 0.6941 | 10.0 | 7460 | 0.6931 | 0.4851 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.1.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1