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

# results

This model is a fine-tuned version of [distilbert-base-cased](https://huggingface.co/distilbert-base-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0452
- Precision: 0.8809
- Recall: 0.9161
- F1: 0.8982
- Accuracy: 0.9860

## 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: 0.0005
- 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 | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.1732        | 1.0   | 2180  | 0.1202          | 0.5106    | 0.6557 | 0.5741 | 0.9612   |
| 0.1057        | 2.0   | 4360  | 0.0821          | 0.6500    | 0.7866 | 0.7118 | 0.9728   |
| 0.0639        | 3.0   | 6540  | 0.0573          | 0.7953    | 0.8256 | 0.8102 | 0.9812   |
| 0.0347        | 4.0   | 8720  | 0.0482          | 0.8531    | 0.9030 | 0.8773 | 0.9846   |
| 0.0212        | 5.0   | 10900 | 0.0452          | 0.8809    | 0.9161 | 0.8982 | 0.9860   |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1