---
library_name: transformers
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: roberta-sentence-classifier
  results: []
---

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

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: 0.6266
- Accuracy: 0.7990
- Macro F1: 0.7614
- Micro F1: 0.7990
- Qwk: 0.6588

## 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: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 4
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step   | Validation Loss | Accuracy | Macro F1 | Micro F1 | Qwk    |
|:-------------:|:-----:|:------:|:---------------:|:--------:|:--------:|:--------:|:------:|
| 0.6267        | 1.0   | 27540  | 0.6108          | 0.7818   | 0.7364   | 0.7818   | 0.6352 |
| 0.5539        | 2.0   | 55080  | 0.5939          | 0.7911   | 0.7498   | 0.7911   | 0.6428 |
| 0.475         | 3.0   | 82620  | 0.6021          | 0.7977   | 0.7592   | 0.7977   | 0.6599 |
| 0.4204        | 4.0   | 110160 | 0.6266          | 0.7990   | 0.7614   | 0.7990   | 0.6588 |


### Framework versions

- Transformers 4.57.3
- Pytorch 2.9.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1