---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
datasets:
- clinc_oos
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
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# distilbert-base-uncased-distilled-clinc

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the clinc_oos dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2366

## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 9

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| No log        | 1.0   | 318  | 1.3258          |
| 1.6434        | 2.0   | 636  | 0.6673          |
| 1.6434        | 3.0   | 954  | 0.3963          |
| 0.6154        | 4.0   | 1272 | 0.2982          |
| 0.3057        | 5.0   | 1590 | 0.2632          |
| 0.3057        | 6.0   | 1908 | 0.2488          |
| 0.231         | 7.0   | 2226 | 0.2425          |
| 0.2073        | 8.0   | 2544 | 0.2382          |
| 0.2073        | 9.0   | 2862 | 0.2366          |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.1.0
- Datasets 1.11.0
- Tokenizers 0.15.1