---
license: apache-2.0
base_model: distilbert/distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- recall
- precision
model-index:
- name: my_fancy_model
  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. -->

# my_fancy_model

This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6695
- Accuracy: 0.65
- Recall: 0.5
- Precision: 0.325

## 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: 5e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Recall | Precision |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|
| No log        | 1.0   | 7    | 0.7025          | 0.65     | 0.5    | 0.325     |
| No log        | 2.0   | 14   | 0.6968          | 0.65     | 0.5    | 0.325     |
| No log        | 3.0   | 21   | 0.8017          | 0.65     | 0.5    | 0.325     |
| No log        | 4.0   | 28   | 0.6836          | 0.65     | 0.5    | 0.325     |
| No log        | 5.0   | 35   | 0.6695          | 0.65     | 0.5    | 0.325     |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1
- Datasets 2.18.0
- Tokenizers 0.15.2