---
library_name: transformers
license: apache-2.0
base_model: distilbert/distilroberta-base
tags:
- generated_from_trainer
- sentiment_analysis
model-index:
- name: go-emotions-fine-tuned-distilroberta
  results: []
datasets:
- google-research-datasets/go_emotions
language:
- en
metrics:
- recall
- precision
- f1
---

<!-- 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. -->

# go-emotions-fine-tuned-distilroberta

This model is a fine-tuned version of [distilbert/distilroberta-base](https://huggingface.co/distilbert/distilroberta-base) on GoEmotions dataset.
It achieves the following results on the evaluation set (threshold = 0.5):
- Loss: 0.0841
- Micro Precision: 0.6789
- Micro Recall: 0.5047
- Micro F1: 0.5790
- Macro Precision: 0.5559
- Macro Recall: 0.4000
- Macro F1: 0.4502
- Weighted Precision: 0.6538
- Weighted Recall: 0.5047
- Weighted F1: 0.5577
- Hamming Loss: 0.0308

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- 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
- num_epochs: 3.0

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Micro Precision | Micro Recall | Micro F1 | Macro Precision | Macro Recall | Macro F1 | Weighted Precision | Weighted Recall | Weighted F1 | Hamming Loss |
|:-------------:|:-----:|:-----:|:---------------:|:---------------:|:------------:|:--------:|:---------------:|:------------:|:--------:|:------------------:|:---------------:|:-----------:|:------------:|
| 0.1062        | 1.0   | 5427  | 0.0889          | 0.6956          | 0.4498       | 0.5464   | 0.5087          | 0.3111       | 0.3537   | 0.6246             | 0.4498          | 0.4936      | 0.0314       |
| 0.0828        | 2.0   | 10854 | 0.0834          | 0.7042          | 0.4798       | 0.5707   | 0.5874          | 0.3562       | 0.4108   | 0.6872             | 0.4798          | 0.5306      | 0.0303       |
| 0.0704        | 3.0   | 16281 | 0.0841          | 0.6789          | 0.5047       | 0.5790   | 0.5559          | 0.4000       | 0.4502   | 0.6538             | 0.5047          | 0.5577      | 0.0308       |

### Test results

| Class             | Precision | Recall | F1-Score | Support |
|-------------------|-----------|--------|----------|---------|
| admiration        | 0.69      | 0.73   | 0.71     | 504     |
| amusement         | 0.79      | 0.87   | 0.83     | 264     |
| anger             | 0.58      | 0.41   | 0.48     | 198     |
| annoyance         | 0.45      | 0.16   | 0.24     | 320     |
| approval          | 0.58      | 0.34   | 0.43     | 351     |
| caring            | 0.51      | 0.29   | 0.37     | 135     |
| confusion         | 0.57      | 0.38   | 0.46     | 153     |
| curiosity         | 0.50      | 0.46   | 0.48     | 284     |
| desire            | 0.70      | 0.36   | 0.48     | 83      |
| disappointment    | 0.60      | 0.19   | 0.28     | 151     |
| disapproval       | 0.42      | 0.29   | 0.34     | 267     |
| disgust           | 0.63      | 0.33   | 0.44     | 123     |
| embarrassment     | 0.82      | 0.38   | 0.52     | 37      |
| excitement        | 0.57      | 0.33   | 0.42     | 103     |
| fear              | 0.71      | 0.64   | 0.68     | 78      |
| gratitude         | 0.94      | 0.90   | 0.92     | 352     |
| grief             | 0.00      | 0.00   | 0.00     | 6       |
| joy               | 0.69      | 0.54   | 0.61     | 161     |
| love              | 0.82      | 0.84   | 0.83     | 238     |
| nervousness       | 0.67      | 0.17   | 0.28     | 23      |
| optimism          | 0.63      | 0.48   | 0.55     | 186     |
| pride             | 0.00      | 0.00   | 0.00     | 16      |
| realization       | 0.54      | 0.13   | 0.21     | 145     |
| relief            | 0.00      | 0.00   | 0.00     | 11      |
| remorse           | 0.58      | 0.77   | 0.66     | 56      |
| sadness           | 0.67      | 0.49   | 0.57     | 156     |
| surprise          | 0.61      | 0.44   | 0.51     | 141     |
| neutral           | 0.73      | 0.54   | 0.62     | 1787    |
| **micro avg**     | 0.68      | 0.51   | 0.58     | 6329    |
| **macro avg**     | 0.57      | 0.41   | 0.46     | 6329    |
| **weighted avg**  | 0.66      | 0.51   | 0.56     | 6329    |
| **samples avg**   | 0.56      | 0.53   | 0.54     | 6329    |


### Framework versions

- Transformers 4.47.0
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.21.0