|
--- |
|
license: mit |
|
base_model: roberta-large |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- accuracy |
|
- f1 |
|
model-index: |
|
- name: roberta-large-detect-dep-v3 |
|
results: [] |
|
--- |
|
|
|
<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
|
should probably proofread and complete it, then remove this comment. --> |
|
|
|
# roberta-large-detect-dep-v3 |
|
|
|
This model is a fine-tuned version of [roberta-large](https://huggingface.co/roberta-large) on the None dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.6207 |
|
- Accuracy: 0.709 |
|
- F1: 0.7820 |
|
|
|
## 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: 8 |
|
- eval_batch_size: 8 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- num_epochs: 3 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| |
|
| 0.6273 | 1.0 | 751 | 0.5776 | 0.731 | 0.7860 | |
|
| 0.5542 | 2.0 | 1502 | 0.5749 | 0.741 | 0.8091 | |
|
| 0.4873 | 3.0 | 2253 | 0.6207 | 0.709 | 0.7820 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.31.0 |
|
- Pytorch 2.0.1+cu118 |
|
- Datasets 2.13.1 |
|
- Tokenizers 0.13.3 |
|
|
