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

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# LLMBook_distilbert-base-uncased-finetuned-emotion

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on [Emotion Dataset](https://github.com/dair-ai/emotion_dataset).
It achieves the following results on the evaluation set:
- Loss: 0.2171
- Accuracy: 0.928
- F1: 0.9279

## 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: 2

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.8356        | 1.0   | 250  | 0.3062          | 0.9115   | 0.9104 |
| 0.2527        | 2.0   | 500  | 0.2171          | 0.928    | 0.9279 |


### Framework versions

- Transformers 4.46.3
- Pytorch 2.3.0+cpu
- Datasets 3.2.0
- Tokenizers 0.20.3