---
library_name: transformers
license: mit
base_model: FacebookAI/roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: my-roberta-RQ3
  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. -->

# my-roberta-RQ3

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: 0.4273
- Accuracy: 0.9480
- F1 Macro: 0.6383
- F1 Weighted: 0.9479

## 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: 64
- eval_batch_size: 64
- 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
- lr_scheduler_warmup_steps: 0.1
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | F1 Weighted |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:-----------:|
| 0.3765        | 1.0   | 539  | 0.3696          | 0.9394   | 0.3048   | 0.9294      |
| 0.3333        | 2.0   | 1078 | 0.3297          | 0.9473   | 0.4082   | 0.9423      |
| 0.2892        | 3.0   | 1617 | 0.3122          | 0.9499   | 0.4966   | 0.9468      |
| 0.2429        | 4.0   | 2156 | 0.3167          | 0.9534   | 0.6575   | 0.9518      |
| 0.1842        | 5.0   | 2695 | 0.3338          | 0.9476   | 0.6299   | 0.9480      |
| 0.1577        | 6.0   | 3234 | 0.3656          | 0.9513   | 0.6632   | 0.9512      |
| 0.1413        | 7.0   | 3773 | 0.3701          | 0.9494   | 0.6440   | 0.9494      |
| 0.1064        | 8.0   | 4312 | 0.4169          | 0.9489   | 0.6454   | 0.9492      |
| 0.1277        | 9.0   | 4851 | 0.4233          | 0.9480   | 0.6350   | 0.9475      |
| 0.0979        | 10.0  | 5390 | 0.4273          | 0.9480   | 0.6383   | 0.9479      |


### Framework versions

- Transformers 5.0.0
- Pytorch 2.10.0+cu128
- Datasets 4.8.3
- Tokenizers 0.22.2