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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: 0.0284
- Accuracy: 0.9931
## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.3359 | 0.1018 | 100 | 0.1977 | 0.9703 |
| 0.17 | 0.2037 | 200 | 0.3161 | 0.9542 |
| 0.1525 | 0.3055 | 300 | 0.0936 | 0.9828 |
| 0.0874 | 0.4073 | 400 | 0.0900 | 0.9863 |
| 0.097 | 0.5092 | 500 | 0.0992 | 0.9863 |
| 0.0874 | 0.6110 | 600 | 0.1275 | 0.9851 |
| 0.0763 | 0.7128 | 700 | 0.1173 | 0.9840 |
| 0.1067 | 0.8147 | 800 | 0.0585 | 0.9874 |
| 0.0646 | 0.9165 | 900 | 0.0358 | 0.9943 |
| 0.0338 | 1.0183 | 1000 | 0.0413 | 0.9943 |
| 0.0463 | 1.1202 | 1100 | 0.0311 | 0.9943 |
| 0.0683 | 1.2220 | 1200 | 0.0473 | 0.9920 |
| 0.0315 | 1.3238 | 1300 | 0.0374 | 0.9931 |
| 0.0251 | 1.4257 | 1400 | 0.0335 | 0.9954 |
| 0.0238 | 1.5275 | 1500 | 0.0481 | 0.9931 |
| 0.0105 | 1.6293 | 1600 | 0.0555 | 0.9931 |
| 0.063 | 1.7312 | 1700 | 0.0343 | 0.9931 |
| 0.0389 | 1.8330 | 1800 | 0.0355 | 0.9931 |
| 0.0463 | 1.9348 | 1900 | 0.0584 | 0.9897 |
| 0.0075 | 2.0367 | 2000 | 0.0284 | 0.9931 |
| 0.0036 | 2.1385 | 2100 | 0.1225 | 0.9760 |
| 0.0062 | 2.2403 | 2200 | 0.0333 | 0.9943 |
| 0.0136 | 2.3422 | 2300 | 0.0379 | 0.9920 |
### Framework versions
- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
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