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---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- clinc_oos
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased-distilled-clinc
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: clinc_oos
type: clinc_oos
args: plus
metrics:
- name: Accuracy
type: accuracy
value: 0.9506451612903226
---
<!-- 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: 0.2466
- Accuracy: 0.9506
## 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: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.9383 | 1.0 | 954 | 1.4511 | 0.8397 |
| 0.8485 | 2.0 | 1908 | 0.4733 | 0.9255 |
| 0.2822 | 3.0 | 2862 | 0.3070 | 0.9429 |
| 0.1515 | 4.0 | 3816 | 0.2664 | 0.9490 |
| 0.106 | 5.0 | 4770 | 0.2641 | 0.95 |
| 0.0874 | 6.0 | 5724 | 0.2536 | 0.9510 |
| 0.0764 | 7.0 | 6678 | 0.2475 | 0.9506 |
| 0.0718 | 8.0 | 7632 | 0.2450 | 0.9513 |
| 0.068 | 9.0 | 8586 | 0.2473 | 0.9497 |
| 0.0664 | 10.0 | 9540 | 0.2466 | 0.9506 |
### Framework versions
- Transformers 4.19.2
- Pytorch 1.11.0
- Datasets 1.16.1
- Tokenizers 0.12.1