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---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased-finetuned-clinc
results: []
---
<!-- 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-finetuned-clinc
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8004
- Accuracy: 0.9152
## 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: 5
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 4.3221 | 1.0 | 318 | 3.3251 | 0.7197 |
| 2.6661 | 2.0 | 636 | 1.9115 | 0.8494 |
| 1.5821 | 3.0 | 954 | 1.1901 | 0.89 |
| 1.0401 | 4.0 | 1272 | 0.8849 | 0.9087 |
| 0.8194 | 5.0 | 1590 | 0.8004 | 0.9152 |
### Framework versions
- Transformers 4.36.2
- Pytorch 1.13.1+cu116
- Datasets 2.16.2.dev0
- Tokenizers 0.15.0
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