---
license: mit
base_model: FacebookAI/roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: roberta-base-CD_baseline
  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-CD_baseline

This model is a fine-tuned version of [FacebookAI/roberta-base](https://huggingface.co/FacebookAI/roberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3012
- Accuracy: 0.5435
- F1: 0.5062
- Precision: 0.5113
- Recall: 0.5435

## 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: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 1.6077        | 1.0   | 125  | 1.6378          | 0.4130   | 0.3268 | 0.2997    | 0.4130 |
| 1.6016        | 2.0   | 250  | 1.4609          | 0.4870   | 0.4109 | 0.3904    | 0.4870 |
| 1.2479        | 3.0   | 375  | 1.4185          | 0.5043   | 0.4485 | 0.4236    | 0.5043 |
| 1.1542        | 4.0   | 500  | 1.3072          | 0.5435   | 0.5141 | 0.5397    | 0.5435 |
| 1.1302        | 5.0   | 625  | 1.3012          | 0.5435   | 0.5062 | 0.5113    | 0.5435 |


### Framework versions

- Transformers 4.38.0
- Pytorch 2.8.0+cu128
- Datasets 4.2.0
- Tokenizers 0.15.2