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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
config: plus
split: validation
args: plus
metrics:
- name: Accuracy
type: accuracy
value: 0.9490322580645161
---
<!-- 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: 0.2988
- Accuracy: 0.9490
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 3.0983 | 1.0 | 318 | 2.2883 | 0.7423 |
| 1.7658 | 2.0 | 636 | 1.1722 | 0.8590 |
| 0.9156 | 3.0 | 954 | 0.6499 | 0.9177 |
| 0.5211 | 4.0 | 1272 | 0.4488 | 0.9326 |
| 0.3488 | 5.0 | 1590 | 0.3661 | 0.9455 |
| 0.267 | 6.0 | 1908 | 0.3309 | 0.9481 |
| 0.226 | 7.0 | 2226 | 0.3132 | 0.9487 |
| 0.2024 | 8.0 | 2544 | 0.3046 | 0.9487 |
| 0.191 | 9.0 | 2862 | 0.3014 | 0.9487 |
| 0.1853 | 10.0 | 3180 | 0.2988 | 0.9490 |
### Framework versions
- Transformers 4.30.0
- Pytorch 2.0.1+cu117
- Datasets 2.14.2
- Tokenizers 0.13.3
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