---
license: apache-2.0
base_model: distilbert/distilbert-base-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: distilbert-base-cased
  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. -->

# distilbert-base-cased

This model is a fine-tuned version of [distilbert/distilbert-base-cased](https://huggingface.co/distilbert/distilbert-base-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0910
- Precision: 0.7563
- Recall: 0.7659
- F1: 0.7610
- Accuracy: 0.9763

## 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: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.151         | 1.0   | 784  | 0.0946          | 0.6986    | 0.7443 | 0.7207 | 0.9711   |
| 0.0391        | 2.0   | 1568 | 0.0859          | 0.7446    | 0.7678 | 0.7560 | 0.9750   |
| 0.0239        | 3.0   | 2352 | 0.0910          | 0.7563    | 0.7659 | 0.7610 | 0.9763   |


### Framework versions

- Transformers 4.39.1
- Pytorch 2.2.1
- Datasets 2.18.0
- Tokenizers 0.15.2