---
library_name: transformers
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: request_classifier
  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. -->

# request_classifier

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: 1.1127
- Accuracy: 0.8148

## 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: 8
- eval_batch_size: 8
- 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: 6
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.8071        | 1.0   | 16   | 1.7437          | 0.4444   |
| 1.7038        | 2.0   | 32   | 1.5904          | 0.6667   |
| 1.5493        | 3.0   | 48   | 1.3934          | 0.7407   |
| 1.3535        | 4.0   | 64   | 1.2310          | 0.7407   |
| 1.1681        | 5.0   | 80   | 1.1331          | 0.8519   |
| 1.1003        | 6.0   | 96   | 1.0971          | 0.8519   |


### Framework versions

- Transformers 4.57.3
- Pytorch 2.9.0+cpu
- Datasets 4.5.0
- Tokenizers 0.22.2