---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: distilbert-base-uncased-finetuned-emotion
  results: []
datasets:
- dair-ai/emotion
---

<!-- 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. -->

# distilbert-base-uncased-finetuned-emotion

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the emotions dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2170
- Accuracy: 0.926
- F1: 0.9261

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

![image/png](https://cdn-uploads.huggingface.co/production/uploads/6595d87eb02e572eb0b28b3d/b3oW_AabCwW0vMF88Yya4.png)

## 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: 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 | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.8047        | 1.0   | 250  | 0.3131          | 0.908    | 0.9073 |
| 0.2397        | 2.0   | 500  | 0.2170          | 0.926    | 0.9261 |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1