pytorch tensorboard distilbert generated_from_trainer dataset:clinc_oos license:apache-2.0 model-index 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: 0.9180645161290323
      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: 0.7721
- Accuracy: 0.9181

## 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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 4.2895        | 1.0   | 318  | 3.2884          | 0.7419   |
| 2.6277        | 2.0   | 636  | 1.8751          | 0.8368   |
| 1.5479        | 3.0   | 954  | 1.1569          | 0.8961   |
| 1.0148        | 4.0   | 1272 | 0.8573          | 0.9132   |
| 0.7952        | 5.0   | 1590 | 0.7721          | 0.9181   |


### Framework versions

- Transformers 4.16.2
- Pytorch 2.4.1+cu121
- Datasets 1.16.1
- Tokenizers 0.19.1
