Donut Base Finetuned Classification
This model is a fine-tuned version of LLMTestSaurav/donut-base-finetuned-classification on the imagefolder dataset.
Fonte do modelo
- Tipo
- CLIP vision
- Tamanho do arquivo
- 772 MB
- Modelo base
- LLMTestSaurav/donut-base-finetuned-classification
- Versão
- vmodel
- Atualizado
- 1 de out. de 2026
- Downloads
- 4
- Fonte
- Hugging Face
Descrição da fonte
donut-base-finetuned-classification
This model is a fine-tuned version of LLMTestSaurav/donut-base-finetuned-classification on the imagefolder dataset.
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: 1
- eval_batch_size: 1
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- training_steps: 30000
- mixed_precision_training: Native AMP
Training results
Framework versions
- Transformers 4.56.1
- Pytorch 2.11.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2
Fontes
1 fonte
Fontes
1 fonteVerificado 1 de out.
Artefatos de modelo
1 artefato
Artefatos de modelo
1 artefatoTrechos de fonte
3 trechos
Trechos de fonte
3 trechos--- library_name: transformers license: mit base_model: LLMTestSaurav/donut-base-finetuned-classification tags: - generated_from_trainer datasets: - imagefolder model-index: - name: donut-base-finetuned-classification 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. --> # donut-base-finetuned-classification This model is a fine-tuned version of [LLMTestSaurav/donut-base-finetuned-classification](https://huggingface.co/LLMTestSaurav/donut-base-finetuned-classification) on the imagefolder dataset. ## 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: 1 - eval_batch_size: 1 - seed: 42 - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: linear - training_steps: 30000 - mixed_precision_training: Native AMP ### Training results ### Framework versions - Transformers 4.56.1 - Pytorch 2.11.0+cu128 - Datasets 4.0.0 - Tokenizers 0.22.2
Source context: 154 downloads · 0 likes · Library transformers · Repo LLMTestSaurav/donut-base-finetuned-classification
Source context: 152 downloads · 0 likes · Library transformers · Repo LLMTestSaurav/donut-base-finetuned-classification
