---
library_name: transformers
license: apache-2.0
base_model: 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-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2719
- Accuracy: 0.9166
- Precision: 0.8914
- Recall: 0.9496
- F1: 0.9195

## 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: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.2355        | 1.0   | 2232 | 0.2344          | 0.9072   | 0.9319    | 0.8795 | 0.9049 |
| 0.1550        | 2.0   | 4464 | 0.2906          | 0.9100   | 0.8825    | 0.9468 | 0.9135 |
| 0.0939        | 3.0   | 6696 | 0.3709          | 0.9115   | 0.9031    | 0.9227 | 0.9128 |


### Framework versions

- Transformers 5.14.1
- Pytorch 2.14.0.dev20260725+cu130
- Datasets 4.0.0
- Tokenizers 0.22.2