---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
base_model: roberta-large
model-index:
- name: roberta-large-go-emotions
  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. -->

# roberta-large-go-emotions

This model is a fine-tuned version of [roberta-large](https://huggingface.co/roberta-large) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0811
- Accuracy: 0.4525
- Precision: 0.5113
- Recall: 0.5202
- F1: 0.5057

## 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: 5e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| No log        | 1.0   | 679  | 0.0936          | 0.4233   | 0.4251    | 0.4021 | 0.3955 |
| 0.1094        | 2.0   | 1358 | 0.0826          | 0.4432   | 0.4828    | 0.4888 | 0.4747 |
| 0.1094        | 3.0   | 2037 | 0.0811          | 0.4525   | 0.5113    | 0.5202 | 0.5057 |


### Framework versions

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