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# distilbert-base-uncased_emotion_ft_12_17

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: 0.1533
- Accuracy: 0.9315
- F1: 0.9317
- Precision: 0.9320
- Recall: 0.9315

## 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: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.8414        | 1.0   | 250  | 0.2936          | 0.9085   | 0.9085 | 0.9097    | 0.9085 |
| 0.2154        | 2.0   | 500  | 0.1816          | 0.9305   | 0.9305 | 0.9313    | 0.9305 |
| 0.1415        | 3.0   | 750  | 0.1597          | 0.9355   | 0.9354 | 0.9356    | 0.9355 |
| 0.1165        | 4.0   | 1000 | 0.1533          | 0.9315   | 0.9317 | 0.9320    | 0.9315 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Tokenizers 0.15.0

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy", "f1", "precision", "recall"], "base_model": "distilbert-base-uncased", "model-index": [{"name": "distilbert-base-uncased_emotion_ft_12_17", "results": []}]}
transformers tensorboard safetensors distilbert text-classification generated_from_trainer base_model:distilbert-base-uncased license:apache-2.0 autotrain_compatible endpoints_compatible region:us