---
library_name: transformers
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
model-index:
- name: emotion_classifier_roberta_optimized
  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_optimized

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: 0.1972
- Macro F1: 0.4889

## 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: 16
- eval_batch_size: 16
- 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_ratio: 0.1
- num_epochs: 7
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Macro F1 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.2093        | 1.0   | 2614  | 0.2019          | 0.4586   |
| 0.1941        | 2.0   | 5228  | 0.1938          | 0.4815   |
| 0.1845        | 3.0   | 7842  | 0.1916          | 0.4921   |
| 0.1764        | 4.0   | 10456 | 0.1928          | 0.4918   |
| 0.1699        | 5.0   | 13070 | 0.1936          | 0.4963   |
| 0.1639        | 6.0   | 15684 | 0.1964          | 0.4872   |
| 0.1608        | 7.0   | 18298 | 0.1972          | 0.4889   |


### Framework versions

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