--- tags: - generated_from_trainer model-index: - name: deit-hoogberta results: [] --- # deit-hoogberta This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 3.5649 - Cer: 0.9892 ## 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: 5e-05 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - gradient_accumulation_steps: 2 - total_train_batch_size: 16 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 3 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Cer | |:-------------:|:-----:|:----:|:---------------:|:------:| | 3.9434 | 0.28 | 500 | 4.0407 | 1.0311 | | 4.0651 | 0.57 | 1000 | 3.8605 | 1.1336 | | 3.8945 | 0.85 | 1500 | 3.7821 | 1.0140 | | 3.5253 | 1.14 | 2000 | 3.7052 | 0.9804 | | 3.5323 | 1.42 | 2500 | 3.6638 | 1.0365 | | 3.3077 | 1.71 | 3000 | 3.6237 | 0.9716 | | 3.3064 | 1.99 | 3500 | 3.5834 | 0.9648 | | 3.2921 | 2.28 | 4000 | 3.5971 | 0.9872 | | 3.0653 | 2.56 | 4500 | 3.5830 | 1.0193 | | 3.1912 | 2.85 | 5000 | 3.5649 | 0.9892 | ### Framework versions - Transformers 4.28.1 - Pytorch 2.0.0+cu118 - Datasets 2.11.0 - Tokenizers 0.13.3