---
library_name: transformers
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
model-index:
- name: xlm-roberta-large_emotion_ft_0416
  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. -->

# xlm-roberta-large_emotion_ft_0416

This model was trained from scratch on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1186
- Accuracy: 0.9415
- F1: 0.9417
- Precision: 0.9177

## 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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Use 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: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|
| 0.8152        | 1.0   | 250  | 0.2905          | 0.902    | 0.9035 | 0.8660    |
| 0.215         | 2.0   | 500  | 0.1572          | 0.941    | 0.9409 | 0.9213    |
| 0.1274        | 3.0   | 750  | 0.1237          | 0.9445   | 0.9453 | 0.9075    |
| 0.101         | 4.0   | 1000 | 0.1186          | 0.9415   | 0.9417 | 0.9177    |


### Framework versions

- Transformers 4.46.3
- Pytorch 2.5.1+cu118
- Datasets 3.1.0
- Tokenizers 0.20.3