metadata
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
datasets:
- data_loader
model-index:
- name: roberta_finetune_model
results: []
roberta_finetune_model
This model is a fine-tuned version of roberta-base on the data_loader dataset. It achieves the following results on the evaluation set:
- Loss: 0.0282
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.0006 | 1.0 | 720 | 0.0326 |
| 0.1065 | 2.0 | 1440 | 0.0324 |
| 0.0001 | 3.0 | 2160 | 0.0282 |
| 0.0 | 4.0 | 2880 | 0.0309 |
| 0.0 | 5.0 | 3600 | 0.0317 |
Framework versions
- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1