---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
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
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# 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: 0.2905
- Accuracy: 0.896
- F1 Score: 0.8962

## 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: 6

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Score |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|
| 1.5116        | 1.0   | 250  | 1.2809          | 0.5315   | 0.4734   |
| 0.8731        | 2.0   | 500  | 0.5533          | 0.834    | 0.8273   |
| 0.4323        | 3.0   | 750  | 0.3940          | 0.863    | 0.8623   |
| 0.2737        | 4.0   | 1000 | 0.3179          | 0.89     | 0.8900   |
| 0.2098        | 5.0   | 1250 | 0.2963          | 0.8935   | 0.8932   |
| 0.1734        | 6.0   | 1500 | 0.2905          | 0.896    | 0.8962   |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Tokenizers 0.19.1