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---
library_name: transformers
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased-survey-category-0.0.1
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-survey-category-0.0.1
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: 0.1004
- Accuracy: 0.9886
## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 20
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log | 1.0 | 232 | 0.1063 | 0.9773 |
| No log | 2.0 | 464 | 0.0811 | 0.9773 |
| 0.2551 | 3.0 | 696 | 0.0704 | 0.9830 |
| 0.2551 | 4.0 | 928 | 0.0903 | 0.9830 |
| 0.0423 | 5.0 | 1160 | 0.0949 | 0.9830 |
| 0.0423 | 6.0 | 1392 | 0.0890 | 0.9886 |
| 0.0268 | 7.0 | 1624 | 0.0916 | 0.9886 |
| 0.0268 | 8.0 | 1856 | 0.1001 | 0.9886 |
| 0.0246 | 9.0 | 2088 | 0.0965 | 0.9886 |
| 0.0246 | 10.0 | 2320 | 0.1002 | 0.9886 |
| 0.0156 | 11.0 | 2552 | 0.0785 | 0.9886 |
| 0.0156 | 12.0 | 2784 | 0.0904 | 0.9886 |
| 0.0157 | 13.0 | 3016 | 0.0825 | 0.9886 |
| 0.0157 | 14.0 | 3248 | 0.0999 | 0.9886 |
| 0.0157 | 15.0 | 3480 | 0.1004 | 0.9886 |
| 0.0137 | 16.0 | 3712 | 0.1020 | 0.9886 |
| 0.0137 | 17.0 | 3944 | 0.1010 | 0.9886 |
| 0.0152 | 18.0 | 4176 | 0.1002 | 0.9886 |
| 0.0152 | 19.0 | 4408 | 0.0999 | 0.9886 |
| 0.0114 | 20.0 | 4640 | 0.1004 | 0.9886 |
### Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0
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