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