---
library_name: transformers
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
model-index:
- name: emotion_classifier_roberta
  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. -->

# emotion_classifier_roberta

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: 0.2388
- Macro F1: 0.3920

## 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: 8
- eval_batch_size: 8
- 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
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Macro F1 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.1963        | 1.0   | 5227  | 0.1933          | 0.3603   |
| 0.1866        | 2.0   | 10454 | 0.1956          | 0.3795   |
| 0.1752        | 3.0   | 15681 | 0.1956          | 0.4092   |
| 0.1696        | 4.0   | 20908 | 0.2009          | 0.4037   |
| 0.1575        | 5.0   | 26135 | 0.2076          | 0.4142   |
| 0.1492        | 6.0   | 31362 | 0.2175          | 0.4077   |
| 0.139         | 7.0   | 36589 | 0.2297          | 0.3932   |
| 0.1274        | 8.0   | 41816 | 0.2388          | 0.3920   |


### Framework versions

- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1