tatr-dataset-1000-500epochs
This model is a fine-tuned version of microsoft/table-transformer-structure-recognition on the None dataset. It achieves the following results on the evaluation set:
- eval_loss: 0.7819
- eval_runtime: 10.4713
- eval_samples_per_second: 13.943
- eval_steps_per_second: 1.814
- epoch: 243.23
- step: 6324
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: 0.0001
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 500
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3
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