---
library_name: transformers
license: apache-2.0
base_model: distilbert/distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
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/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1181
- Accuracy: 0.9667
- Precision: 0.9687
- Recall: 0.9667
- F1: 0.9666

## 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: 3e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 5
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.2806        | 0.9895 | 59   | 0.2562          | 0.8833   | 0.8896    | 0.8833 | 0.8824 |
| 0.047         | 1.9958 | 119  | 0.1286          | 0.9583   | 0.9596    | 0.9583 | 0.9584 |
| 0.0946        | 2.9853 | 178  | 0.1196          | 0.9667   | 0.9672    | 0.9667 | 0.9667 |
| 0.0037        | 3.9916 | 238  | 0.1181          | 0.9667   | 0.9687    | 0.9667 | 0.9666 |
| 0.0021        | 4.9979 | 298  | 0.1189          | 0.9667   | 0.9671    | 0.9667 | 0.9666 |
| 0.0039        | 5.9874 | 357  | 0.1515          | 0.9667   | 0.9672    | 0.9667 | 0.9667 |
| 0.0013        | 6.9937 | 417  | 0.1703          | 0.9667   | 0.9667    | 0.9667 | 0.9667 |
| 0.0012        | 8.0    | 477  | 0.1703          | 0.9583   | 0.9585    | 0.9583 | 0.9583 |
| 0.0011        | 8.9895 | 536  | 0.1841          | 0.9667   | 0.9672    | 0.9667 | 0.9667 |
| 0.001         | 9.8952 | 590  | 0.1797          | 0.9667   | 0.9672    | 0.9667 | 0.9667 |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.5.0+cu121
- Datasets 3.0.2
- Tokenizers 0.19.1