metadata
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: roberta-base-Dep
results: []
roberta-base-Dep
This model is a fine-tuned version of roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3838
- Accuracy: 0.8383
- F1: 0.9031
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-06
- 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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| No log | 1.0 | 235 | 0.3545 | 0.8567 | 0.9196 |
| No log | 2.0 | 470 | 0.3505 | 0.8567 | 0.9183 |
| 0.388 | 3.0 | 705 | 0.4525 | 0.78 | 0.8608 |
| 0.388 | 4.0 | 940 | 0.3853 | 0.83 | 0.8976 |
| 0.3048 | 5.0 | 1175 | 0.3838 | 0.8383 | 0.9031 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3