---
library_name: transformers
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased-finetuned-clinc
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# distilbert-base-uncased-finetuned-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: 0.8032
- Accuracy: 0.9168

## 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 with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 4.3135        | 1.0   | 318  | 3.3064          | 0.7216   |
| 2.6572        | 2.0   | 636  | 1.9022          | 0.8461   |
| 1.5805        | 3.0   | 954  | 1.1884          | 0.8868   |
| 1.0451        | 4.0   | 1272 | 0.8897          | 0.9090   |
| 0.8252        | 5.0   | 1590 | 0.8032          | 0.9168   |


### Framework versions

- Transformers 4.46.0
- Pytorch 2.5.0
- Datasets 3.0.2
- Tokenizers 0.20.1