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

# cnnroberta

This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7735
- F1: 0.0
- Precision: 0.0
- Recall: 0.0
- Accuracy: 0.7446

## 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-05
- train_batch_size: 32
- eval_batch_size: 32
- 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: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1  | Precision | Recall | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---:|:---------:|:------:|:--------:|
| 0.5531        | 1.0   | 583  | 0.7817          | 0.0 | 0.0       | 0.0    | 0.7332   |
| 0.5727        | 2.0   | 1166 | 0.6993          | 0.0 | 0.0       | 0.0    | 0.7660   |
| 0.5215        | 3.0   | 1749 | 0.7671          | 0.0 | 0.0       | 0.0    | 0.7416   |
| 0.4454        | 4.0   | 2332 | 0.7735          | 0.0 | 0.0       | 0.0    | 0.7446   |


### Framework versions

- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Tokenizers 0.21.0