---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
base_model: distilbert-base-uncased
model-index:
- name: FT_DistilBERT
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# FT_DistilBERT

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: 0.2519
- Accuracy: 0.8892
- F1: 0.8892
- Precision: 0.8904
- Recall: 0.8900

## 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: 16
- eval_batch_size: 16
- 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 | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.3172        | 1.0   | 1000 | 0.2984          | 0.8745   | 0.8740 | 0.8772    | 0.8734 |
| 0.2419        | 2.0   | 2000 | 0.2519          | 0.8892   | 0.8892 | 0.8904    | 0.8900 |
| 0.2102        | 3.0   | 3000 | 0.2963          | 0.8955   | 0.8955 | 0.8960    | 0.8960 |
| 0.1679        | 4.0   | 4000 | 0.3012          | 0.9005   | 0.9004 | 0.9007    | 0.9002 |
| 0.1569        | 5.0   | 5000 | 0.3147          | 0.8958   | 0.8957 | 0.8958    | 0.8956 |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2