|
|
--- |
|
|
library_name: transformers |
|
|
license: mit |
|
|
base_model: FacebookAI/roberta-base |
|
|
tags: |
|
|
- generated_from_trainer |
|
|
metrics: |
|
|
- precision |
|
|
- recall |
|
|
- accuracy |
|
|
model-index: |
|
|
- name: roberta-base-pr |
|
|
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-base-pr |
|
|
|
|
|
This model is a fine-tuned version of [FacebookAI/roberta-base](https://huggingface.co/FacebookAI/roberta-base) on the None dataset. |
|
|
It achieves the following results on the evaluation set: |
|
|
- Loss: 1.1841 |
|
|
- F1 Macro: 0.6097 |
|
|
- Precision: 0.6135 |
|
|
- Recall: 0.6205 |
|
|
- Accuracy: 0.7627 |
|
|
|
|
|
## 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: 32 |
|
|
- seed: 42 |
|
|
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
|
|
- lr_scheduler_type: linear |
|
|
- lr_scheduler_warmup_ratio: 0.1 |
|
|
- num_epochs: 20 |
|
|
|
|
|
### Training results |
|
|
|
|
|
| Training Loss | Epoch | Step | Validation Loss | F1 Macro | Precision | Recall | Accuracy | |
|
|
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:--------:| |
|
|
| No log | 1.0 | 240 | 2.3617 | 0.0348 | 0.1449 | 0.1032 | 0.0749 | |
|
|
| No log | 2.0 | 480 | 0.8375 | 0.5802 | 0.5865 | 0.6081 | 0.7399 | |
|
|
| 1.9571 | 3.0 | 720 | 0.8221 | 0.5996 | 0.6040 | 0.6244 | 0.7471 | |
|
|
| 1.9571 | 4.0 | 960 | 0.8073 | 0.6168 | 0.6096 | 0.6356 | 0.7617 | |
|
|
| 0.9292 | 5.0 | 1200 | 0.7768 | 0.6273 | 0.6273 | 0.6369 | 0.7742 | |
|
|
| 0.9292 | 6.0 | 1440 | 0.9650 | 0.6009 | 0.6025 | 0.6211 | 0.7445 | |
|
|
| 0.5053 | 7.0 | 1680 | 1.0663 | 0.6072 | 0.6218 | 0.6186 | 0.7622 | |
|
|
| 0.5053 | 8.0 | 1920 | 1.1841 | 0.6097 | 0.6135 | 0.6205 | 0.7627 | |
|
|
|
|
|
|
|
|
### Framework versions |
|
|
|
|
|
- Transformers 4.57.1 |
|
|
- Pytorch 2.8.0+cu128 |
|
|
- Datasets 4.4.1 |
|
|
- Tokenizers 0.22.1 |
|
|
|
