---
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: roberta_base_results_batch_size16_512max_length
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# roberta_base_results_batch_size16_512max_length

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: 0.3161
- Accuracy: 0.8660
- F1: 0.8650

## 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: 2
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|
| 0.4934        | 0.5319 | 100  | 0.3533          | 0.8571   | 0.8543 |
| 0.3437        | 1.0638 | 200  | 0.3645          | 0.8542   | 0.8540 |
| 0.2924        | 1.5957 | 300  | 0.3161          | 0.8660   | 0.8650 |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1