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---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
datasets:
- clinc_oos
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased-distilled-optim-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: 0.9448387096774193
---
<!-- 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-optim-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: 0.3314
- Accuracy: 0.9448
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log | 1.0 | 318 | 2.1746 | 0.7242 |
| 2.5724 | 2.0 | 636 | 1.1166 | 0.8623 |
| 2.5724 | 3.0 | 954 | 0.6319 | 0.9155 |
| 0.9951 | 4.0 | 1272 | 0.4582 | 0.9306 |
| 0.4397 | 5.0 | 1590 | 0.3865 | 0.9394 |
| 0.4397 | 6.0 | 1908 | 0.3583 | 0.9419 |
| 0.2978 | 7.0 | 2226 | 0.3445 | 0.9429 |
| 0.251 | 8.0 | 2544 | 0.3394 | 0.9426 |
| 0.251 | 9.0 | 2862 | 0.3334 | 0.9445 |
| 0.233 | 10.0 | 3180 | 0.3314 | 0.9448 |
### Framework versions
- Transformers 4.36.2
- Pytorch 2.1.1+cu118
- Datasets 2.16.1
- Tokenizers 0.15.0
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