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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: 0.9503225806451613
---
<!-- 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: 0.2869
- 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: 48
- eval_batch_size: 48
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.026785267717638298
- num_epochs: 24
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log | 1.0 | 318 | 2.1228 | 0.7194 |
| 2.5433 | 2.0 | 636 | 0.8036 | 0.8935 |
| 2.5433 | 3.0 | 954 | 0.4630 | 0.9355 |
| 0.7139 | 4.0 | 1272 | 0.3767 | 0.9429 |
| 0.3352 | 5.0 | 1590 | 0.3417 | 0.9461 |
| 0.3352 | 6.0 | 1908 | 0.3249 | 0.95 |
| 0.2555 | 7.0 | 2226 | 0.3141 | 0.9487 |
| 0.2237 | 8.0 | 2544 | 0.3089 | 0.9490 |
| 0.2237 | 9.0 | 2862 | 0.3039 | 0.9487 |
| 0.2098 | 10.0 | 3180 | 0.3040 | 0.9487 |
| 0.2098 | 11.0 | 3498 | 0.2971 | 0.9516 |
| 0.2004 | 12.0 | 3816 | 0.2945 | 0.95 |
| 0.1949 | 13.0 | 4134 | 0.2967 | 0.9468 |
| 0.1949 | 14.0 | 4452 | 0.2912 | 0.9497 |
| 0.1905 | 15.0 | 4770 | 0.2907 | 0.9513 |
| 0.1883 | 16.0 | 5088 | 0.2927 | 0.9487 |
| 0.1883 | 17.0 | 5406 | 0.2901 | 0.9503 |
| 0.1852 | 18.0 | 5724 | 0.2879 | 0.9497 |
| 0.184 | 19.0 | 6042 | 0.2895 | 0.95 |
| 0.184 | 20.0 | 6360 | 0.2876 | 0.9519 |
| 0.1828 | 21.0 | 6678 | 0.2871 | 0.9503 |
| 0.1828 | 22.0 | 6996 | 0.2867 | 0.9510 |
| 0.1816 | 23.0 | 7314 | 0.2868 | 0.9503 |
| 0.1813 | 24.0 | 7632 | 0.2869 | 0.9503 |
### Framework versions
- Transformers 4.16.2
- Pytorch 2.4.1+cu121
- Datasets 1.16.1
- Tokenizers 0.19.1
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