transformers pytorch 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-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: 0.9493548387096774
      name: Accuracy
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# 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: 0.3288
- Accuracy: 0.9494

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 3.9476        | 1.0   | 318  | 2.9510          | 0.7468   |
| 2.2551        | 2.0   | 636  | 1.4760          | 0.8555   |
| 1.1113        | 3.0   | 954  | 0.7582          | 0.9126   |
| 0.5674        | 4.0   | 1272 | 0.4822          | 0.9326   |
| 0.3386        | 5.0   | 1590 | 0.3837          | 0.9435   |
| 0.2399        | 6.0   | 1908 | 0.3515          | 0.9432   |
| 0.1951        | 7.0   | 2226 | 0.3370          | 0.9465   |
| 0.1736        | 8.0   | 2544 | 0.3320          | 0.9468   |
| 0.1631        | 9.0   | 2862 | 0.3286          | 0.9471   |
| 0.1575        | 10.0  | 3180 | 0.3288          | 0.9494   |


### Framework versions

- Transformers 4.28.1
- Pytorch 2.1.0.dev20230502
- Datasets 2.12.0
- Tokenizers 0.13.3
