---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
base_model: Prasadrao/xlm-roberta-large-go-emotions-v2
model-index:
- name: xlm-roberta-large-go-emotions-v3
  results: []
datasets:
- go_emotions
---

<!-- 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-go-emotions-v3

This model is a fine-tuned version of [Prasadrao/xlm-roberta-large-go-emotions-v2](https://huggingface.co/Prasadrao/xlm-roberta-large-go-emotions-v2) on go emotion dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0953
- Accuracy: 0.4534
- Precision: 0.5400
- Recall: 0.5187
- F1: 0.5151

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| No log        | 1.0   | 1357 | 0.0929          | 0.4624   | 0.5267    | 0.5037 | 0.5051 |
| 0.0467        | 2.0   | 2714 | 0.0953          | 0.4534   | 0.5400    | 0.5187 | 0.5151 |


### Framework versions

- Transformers 4.37.0
- Pytorch 2.1.2
- Datasets 2.15.0
- Tokenizers 0.15.1