---
base_model: distilbert-base-uncased
license: apache-2.0
metrics:
- accuracy
tags:
- generated_from_trainer
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: 0.3068
- Accuracy: 0.9085
- F1 Score: 0.9086

## 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 Score |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|
| 0.9641        | 1.0   | 250  | 0.6194          | 0.792    | 0.7819   |
| 0.4398        | 2.0   | 500  | 0.3389          | 0.883    | 0.8825   |
| 0.258         | 3.0   | 750  | 0.2948          | 0.8945   | 0.8951   |
| 0.1744        | 4.0   | 1000 | 0.2841          | 0.9035   | 0.9038   |
| 0.132         | 5.0   | 1250 | 0.2937          | 0.8985   | 0.8983   |
| 0.1078        | 6.0   | 1500 | 0.2770          | 0.9055   | 0.9054   |
| 0.0888        | 7.0   | 1750 | 0.3017          | 0.903    | 0.9028   |
| 0.0739        | 8.0   | 2000 | 0.2829          | 0.9095   | 0.9096   |
| 0.0611        | 9.0   | 2250 | 0.3062          | 0.91     | 0.9102   |
| 0.0506        | 10.0  | 2500 | 0.3068          | 0.9085   | 0.9086   |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Tokenizers 0.19.1