---
library_name: transformers
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: []
---

<!-- 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 an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2291
- Accuracy: 0.9395
- F1: 0.9395

## 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: 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.1313        | 1.0   | 250  | 0.1574          | 0.9355   | 0.9359 |
| 0.0897        | 2.0   | 500  | 0.1597          | 0.9375   | 0.9368 |
| 0.0818        | 3.0   | 750  | 0.1496          | 0.9395   | 0.9401 |
| 0.068         | 4.0   | 1000 | 0.1707          | 0.9365   | 0.9366 |
| 0.0533        | 5.0   | 1250 | 0.1842          | 0.9365   | 0.9363 |
| 0.043         | 6.0   | 1500 | 0.2020          | 0.9365   | 0.9363 |
| 0.0325        | 7.0   | 1750 | 0.2172          | 0.936    | 0.9359 |
| 0.0279        | 8.0   | 2000 | 0.2262          | 0.9355   | 0.9353 |
| 0.0207        | 9.0   | 2250 | 0.2238          | 0.939    | 0.9392 |
| 0.0188        | 10.0  | 2500 | 0.2291          | 0.9395   | 0.9395 |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1