layoutlmv2-large-uncased-finetuned-infovqa
This model is a fine-tuned version of microsoft/layoutlmv2-large-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.2207
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: 2
- eval_batch_size: 2
- seed: 250500
- 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 |
---|---|---|---|
4.1829 | 0.08 | 500 | 3.6339 |
3.5002 | 0.16 | 1000 | 3.0721 |
2.9556 | 0.24 | 1500 | 2.8731 |
2.8939 | 0.33 | 2000 | 3.1566 |
2.6986 | 0.41 | 2500 | 3.1023 |
2.7569 | 0.49 | 3000 | 2.7743 |
2.6391 | 0.57 | 3500 | 2.5023 |
2.4277 | 0.65 | 4000 | 2.5465 |
2.4242 | 0.73 | 4500 | 2.4709 |
2.3978 | 0.82 | 5000 | 2.4019 |
2.2653 | 0.9 | 5500 | 2.3383 |
2.3916 | 0.98 | 6000 | 2.4765 |
1.9423 | 1.06 | 6500 | 2.3798 |
1.8538 | 1.14 | 7000 | 2.3628 |
1.8136 | 1.22 | 7500 | 2.3671 |
1.7808 | 1.31 | 8000 | 2.5585 |
1.7772 | 1.39 | 8500 | 2.5862 |
1.755 | 1.47 | 9000 | 2.3105 |
1.6529 | 1.55 | 9500 | 2.2417 |
1.6956 | 1.63 | 10000 | 2.1755 |
1.5713 | 1.71 | 10500 | 2.2917 |
1.565 | 1.79 | 11000 | 2.0838 |
1.615 | 1.88 | 11500 | 2.2111 |
1.5249 | 1.96 | 12000 | 2.2207 |
Framework versions
- Transformers 4.12.3
- Pytorch 1.8.0+cu101
- Datasets 1.15.1
- Tokenizers 0.10.3
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