---
library_name: transformers
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased-distilled-clinc
  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-uncased-distilled-clinc

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: 0.2930
- Accuracy: 0.9442

## 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: 48
- eval_batch_size: 48
- 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 318  | 1.8192          | 0.7226   |
| 2.1793        | 2.0   | 636  | 0.9289          | 0.8658   |
| 2.1793        | 3.0   | 954  | 0.5369          | 0.9148   |
| 0.8368        | 4.0   | 1272 | 0.3926          | 0.9323   |
| 0.3884        | 5.0   | 1590 | 0.3367          | 0.9384   |
| 0.3884        | 6.0   | 1908 | 0.3173          | 0.9423   |
| 0.2725        | 7.0   | 2226 | 0.3054          | 0.9445   |
| 0.2365        | 8.0   | 2544 | 0.2980          | 0.9439   |
| 0.2365        | 9.0   | 2862 | 0.2948          | 0.9452   |
| 0.2235        | 10.0  | 3180 | 0.2930          | 0.9442   |


### Framework versions

- Transformers 4.56.1
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.0