DeepFake-EN-B6 / README.md
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---
license: apache-2.0
base_model: google/efficientnet-b6
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: DeepFake-EN-B6
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. -->
# DeepFake-EN-B6
This model is a fine-tuned version of [google/efficientnet-b6](https://huggingface.co/google/efficientnet-b6) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0036
- Accuracy: 0.9989
## 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: 3e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 2.5
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.0076 | 0.9998 | 2187 | 0.0088 | 0.9970 |
| 0.002 | 2.0 | 4375 | 0.0173 | 0.9931 |
| 0.0011 | 2.4997 | 5468 | 0.0036 | 0.9989 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.19.2
- Tokenizers 0.19.1