---
library_name: transformers
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: model
  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. -->

# model

This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 3.7669
- Precision: 0.2852
- Recall: 0.2420
- F1: 0.2618
- Accuracy: 0.8806

## 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: 4
- eval_batch_size: 4
- 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 | Precision | Recall | F1     | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.0387        | 0.4292 | 100  | 3.2626          | 0.2781    | 0.2316 | 0.2527 | 0.8801   |
| 0.0432        | 0.8584 | 200  | 4.3510          | 0.3575    | 0.1485 | 0.2098 | 0.9021   |
| 0.0305        | 1.2876 | 300  | 4.4340          | 0.3663    | 0.1578 | 0.2206 | 0.9024   |
| 0.0303        | 1.7167 | 400  | 4.2810          | 0.3418    | 0.1537 | 0.2120 | 0.9000   |
| 0.0347        | 2.1459 | 500  | 4.3217          | 0.3607    | 0.1828 | 0.2426 | 0.9001   |
| 0.0235        | 2.5751 | 600  | 4.3738          | 0.3302    | 0.1817 | 0.2344 | 0.8961   |


### Framework versions

- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0