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---
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 |