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---

license: apache-2.0
tags:
- generated_from_trainer
datasets:
- clinc_oos
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased-finetuned-clinc
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: clinc_oos
      type: clinc_oos
      args: plus
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.9170967741935484
---


<!-- 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-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: 0.7778

- Accuracy: 0.9171



## 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 |

|:-------------:|:-----:|:----:|:---------------:|:--------:|

| 4.2882        | 1.0   | 318  | 3.2777          | 0.7390   |

| 2.6228        | 2.0   | 636  | 1.8739          | 0.8287   |

| 1.5439        | 3.0   | 954  | 1.1619          | 0.8894   |

| 1.0111        | 4.0   | 1272 | 0.8601          | 0.9094   |

| 0.7999        | 5.0   | 1590 | 0.7778          | 0.9171   |





### Framework versions



- Transformers 4.11.3

- Pytorch 1.12.1+cpu

- Datasets 2.4.0

- Tokenizers 0.10.3