transformers pytorch distilbert text-classification generated_from_trainer dataset:clinc_oos base_model:distilbert/distilbert-base-uncased base_model:finetune:distilbert/distilbert-base-uncased license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
---
base_model: distilbert-base-uncased
datasets:
- clinc_oos
license: apache-2.0
metrics:
- accuracy
tags:
- generated_from_trainer
model-index:
- name: distilbert-base-uncased-distilled-clinc
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: clinc_oos
      type: clinc_oos
      config: plus
      split: validation
      args: plus
    metrics:
    - type: accuracy
      value: 0.9451612903225807
      name: Accuracy
---

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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: 0.2695
- Accuracy: 0.9452

## 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.2521        | 1.0   | 318  | 1.5880          | 0.7184   |
| 1.2228        | 2.0   | 636  | 0.7961          | 0.8648   |
| 0.647         | 3.0   | 954  | 0.4671          | 0.9184   |
| 0.3987        | 4.0   | 1272 | 0.3505          | 0.9358   |
| 0.2955        | 5.0   | 1590 | 0.3058          | 0.9410   |
| 0.2513        | 6.0   | 1908 | 0.2863          | 0.9452   |
| 0.231         | 7.0   | 2226 | 0.2785          | 0.9461   |
| 0.2194        | 8.0   | 2544 | 0.2733          | 0.9461   |
| 0.213         | 9.0   | 2862 | 0.2709          | 0.9452   |
| 0.2099        | 10.0  | 3180 | 0.2695          | 0.9452   |


### Framework versions

- Transformers 4.34.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.14.0
