transformers pytorch tensorboard distilbert text-classification generated_from_trainer dataset:clinc_oos license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
---
datasets:
- clinc_oos
license: apache-2.0
metrics:
- accuracy
tags:
- generated_from_trainer
model-index:
- name: distilbert-base-uncased-finetuned-clinc
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: clinc_oos
      type: clinc_oos
      args: plus
    metrics:
    - type: accuracy
      value: 0.9474193548387096
      name: Accuracy
---

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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 the clinc_oos dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2454
- Accuracy: 0.9474

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 3.496         | 1.0   | 954  | 1.8019          | 0.8306   |
| 1.0663        | 2.0   | 1908 | 0.5690          | 0.9174   |
| 0.3267        | 3.0   | 2862 | 0.3128          | 0.9406   |
| 0.1397        | 4.0   | 3816 | 0.2567          | 0.9445   |
| 0.0846        | 5.0   | 4770 | 0.2454          | 0.9474   |


### Framework versions

- Transformers 4.19.2
- Pytorch 1.11.0
- Datasets 1.16.1
- Tokenizers 0.12.1
