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---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert_EPU
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_EPU
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: 1.0592
- Accuracy: 0.7291
## 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: 1e-05
- train_batch_size: 6
- eval_batch_size: 6
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 12
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.4904 | 1.0 | 699 | 0.5631 | 0.7077 |
| 0.5241 | 2.0 | 1398 | 0.5150 | 0.7458 |
| 0.3692 | 3.0 | 2097 | 0.5419 | 0.7501 |
| 0.3366 | 4.0 | 2796 | 0.6243 | 0.7430 |
| 0.2657 | 5.0 | 3495 | 0.7257 | 0.7358 |
| 0.2303 | 6.0 | 4194 | 0.8840 | 0.7349 |
| 0.0503 | 7.0 | 4893 | 1.0307 | 0.7291 |
| 0.0732 | 8.0 | 5592 | 1.0592 | 0.7291 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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