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

# trainer_output

This model is a fine-tuned version of [FacebookAI/roberta-base](https://huggingface.co/FacebookAI/roberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1273
- Accuracy: 0.9751
- F1: 0.9751
- Precision: 0.9751
- Recall: 0.9751

## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH 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: 573
- num_epochs: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.1262        | 1.0   | 1147 | 0.1067          | 0.9618   | 0.9618 | 0.9618    | 0.9618 |
| 0.0909        | 2.0   | 2294 | 0.1082          | 0.9656   | 0.9653 | 0.9665    | 0.9656 |
| 0.0688        | 3.0   | 3441 | 0.0899          | 0.9727   | 0.9727 | 0.9729    | 0.9727 |
| 0.0435        | 4.0   | 4588 | 0.0971          | 0.9769   | 0.9769 | 0.9769    | 0.9769 |
| 0.0405        | 5.0   | 5735 | 0.1163          | 0.9771   | 0.9771 | 0.9771    | 0.9771 |


### Framework versions

- Transformers 4.52.4
- Pytorch 2.6.0+cu124
- Datasets 2.14.4
- Tokenizers 0.21.1