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---
license: apache-2.0
base_model: distilbert-base-uncased-distilled-squad
tags:
- generated_from_trainer
datasets:
- clinc_oos
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased-distilled-squad-finetuned-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: 0.8722580645161291
---
<!-- 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-squad-finetuned-clinc
This model is a fine-tuned version of [distilbert-base-uncased-distilled-squad](https://huggingface.co/distilbert-base-uncased-distilled-squad) on the clinc_oos dataset.
It achieves the following results on the evaluation set:
- Loss: 1.7920
- Accuracy: 0.8723
## 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: 384
- eval_batch_size: 384
- 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 | 40 | 3.7816 | 0.2016 |
| No log | 2.0 | 80 | 3.3589 | 0.5374 |
| No log | 3.0 | 120 | 2.9695 | 0.6955 |
| No log | 4.0 | 160 | 2.6408 | 0.7726 |
| No log | 5.0 | 200 | 2.3697 | 0.8145 |
| No log | 6.0 | 240 | 2.1547 | 0.8426 |
| No log | 7.0 | 280 | 1.9912 | 0.8529 |
| 2.8639 | 8.0 | 320 | 1.8802 | 0.8645 |
| 2.8639 | 9.0 | 360 | 1.8138 | 0.8706 |
| 2.8639 | 10.0 | 400 | 1.7920 | 0.8723 |
### Framework versions
- Transformers 4.32.1
- Pytorch 2.1.0
- Datasets 2.14.6
- Tokenizers 0.13.3
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