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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: train
args: plus
metrics:
- name: Accuracy
type: accuracy
value: 0.9503225806451613
---
<!-- 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: 0.2656
- Accuracy: 0.9503
## 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: 12
- eval_batch_size: 12
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 9
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 3.1212 | 1.0 | 1271 | 1.2698 | 0.8558 |
| 0.6441 | 2.0 | 2542 | 0.3528 | 0.9326 |
| 0.149 | 3.0 | 3813 | 0.2512 | 0.9494 |
| 0.0647 | 4.0 | 5084 | 0.2510 | 0.95 |
| 0.0406 | 5.0 | 6355 | 0.2575 | 0.9510 |
| 0.0318 | 6.0 | 7626 | 0.2592 | 0.9494 |
| 0.026 | 7.0 | 8897 | 0.2629 | 0.9503 |
| 0.023 | 8.0 | 10168 | 0.2682 | 0.95 |
| 0.0207 | 9.0 | 11439 | 0.2656 | 0.9503 |
### Framework versions
- Transformers 4.21.3
- Pytorch 1.12.1
- Datasets 2.4.0
- Tokenizers 0.12.1
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