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---
library_name: transformers
license: mit
base_model: FacebookAI/roberta-large
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: fine_tuned_main_raid
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. -->
# fine_tuned_main_raid
This model is a fine-tuned version of [FacebookAI/roberta-large](https://huggingface.co/FacebookAI/roberta-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0407
- Accuracy: 0.9922
## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.3543 | 0.0767 | 100 | 0.1765 | 0.9655 |
| 0.1516 | 0.1534 | 200 | 0.1955 | 0.9724 |
| 0.1415 | 0.2301 | 300 | 0.1323 | 0.9724 |
| 0.2002 | 0.3067 | 400 | 0.0993 | 0.9716 |
| 0.1057 | 0.3834 | 500 | 0.2031 | 0.9552 |
| 0.0734 | 0.4601 | 600 | 0.1010 | 0.9802 |
| 0.0725 | 0.5368 | 700 | 0.1511 | 0.9767 |
| 0.1326 | 0.6135 | 800 | 0.0607 | 0.9879 |
| 0.0667 | 0.6902 | 900 | 0.0734 | 0.9845 |
| 0.1132 | 0.7669 | 1000 | 0.0878 | 0.9819 |
| 0.0731 | 0.8436 | 1100 | 0.0694 | 0.9888 |
| 0.0678 | 0.9202 | 1200 | 0.0704 | 0.9853 |
| 0.0455 | 0.9969 | 1300 | 0.0522 | 0.9905 |
| 0.0656 | 1.0736 | 1400 | 0.0646 | 0.9871 |
| 0.0463 | 1.1503 | 1500 | 0.0407 | 0.9922 |
| 0.0432 | 1.2270 | 1600 | 0.0646 | 0.9897 |
| 0.0347 | 1.3037 | 1700 | 0.0421 | 0.9931 |
| 0.0361 | 1.3804 | 1800 | 0.0420 | 0.9931 |
### Framework versions
- Transformers 4.46.2
- Pytorch 2.5.0+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
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