---
library_name: transformers
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
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: 0.1401
- Accuracy: 0.937
- F1: 0.9371
- Precision: 0.9375
- Recall: 0.937

## 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: 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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.204         | 1.0   | 250  | 0.1767          | 0.9285   | 0.9294 | 0.9323    | 0.9285 |
| 0.1361        | 2.0   | 500  | 0.1595          | 0.93     | 0.9306 | 0.9330    | 0.93   |
| 0.1057        | 3.0   | 750  | 0.1460          | 0.9375   | 0.9383 | 0.9406    | 0.9375 |
| 0.0836        | 4.0   | 1000 | 0.1384          | 0.9405   | 0.9405 | 0.9408    | 0.9405 |
| 0.069         | 5.0   | 1250 | 0.1401          | 0.937    | 0.9371 | 0.9375    | 0.937  |


### Framework versions

- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0