# Load model directly
from transformers import AutoProcessor, AutoModelForDocumentQuestionAnswering
processor = AutoProcessor.from_pretrained("Nefertury/test_test_42")
model = AutoModelForDocumentQuestionAnswering.from_pretrained("Nefertury/test_test_42")Quick Links
test_test_42
This model is a fine-tuned version of microsoft/layoutlmv2-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 5.1019
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: 4
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 5.4532 | 2.0 | 50 | 5.1019 |
Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1
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Model tree for Nefertury/test_test_42
Base model
microsoft/layoutlmv2-base-uncased
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("document-question-answering", model="Nefertury/test_test_42")