|
--- |
|
license: cc-by-nc-sa-4.0 |
|
tags: |
|
- generated_from_trainer |
|
model-index: |
|
- name: layoutlmv2-large-uncased-finetuned-vi-infovqa |
|
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. --> |
|
|
|
# layoutlmv2-large-uncased-finetuned-vi-infovqa |
|
|
|
This model is a fine-tuned version of [microsoft/layoutlmv2-large-uncased](https://huggingface.co/microsoft/layoutlmv2-large-uncased) on an unknown dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 8.5806 |
|
|
|
## 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: 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: 6 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | |
|
|:-------------:|:-----:|:----:|:---------------:| |
|
| No log | 0.17 | 100 | 4.6181 | |
|
| No log | 0.33 | 200 | 4.3357 | |
|
| No log | 0.5 | 300 | 4.3897 | |
|
| No log | 0.66 | 400 | 4.8238 | |
|
| 4.4277 | 0.83 | 500 | 3.9088 | |
|
| 4.4277 | 0.99 | 600 | 3.6063 | |
|
| 4.4277 | 1.16 | 700 | 3.4278 | |
|
| 4.4277 | 1.32 | 800 | 3.5428 | |
|
| 4.4277 | 1.49 | 900 | 3.4331 | |
|
| 3.0413 | 1.65 | 1000 | 3.3699 | |
|
| 3.0413 | 1.82 | 1100 | 3.3622 | |
|
| 3.0413 | 1.98 | 1200 | 3.5294 | |
|
| 3.0413 | 2.15 | 1300 | 3.7918 | |
|
| 3.0413 | 2.31 | 1400 | 3.4007 | |
|
| 2.0843 | 2.48 | 1500 | 4.0296 | |
|
| 2.0843 | 2.64 | 1600 | 4.1852 | |
|
| 2.0843 | 2.81 | 1700 | 3.6690 | |
|
| 2.0843 | 2.97 | 1800 | 3.6089 | |
|
| 2.0843 | 3.14 | 1900 | 5.5534 | |
|
| 1.7527 | 3.3 | 2000 | 4.7498 | |
|
| 1.7527 | 3.47 | 2100 | 5.2691 | |
|
| 1.7527 | 3.63 | 2200 | 5.1324 | |
|
| 1.7527 | 3.8 | 2300 | 4.5912 | |
|
| 1.7527 | 3.96 | 2400 | 4.1727 | |
|
| 1.2037 | 4.13 | 2500 | 6.1174 | |
|
| 1.2037 | 4.29 | 2600 | 5.7172 | |
|
| 1.2037 | 4.46 | 2700 | 5.8843 | |
|
| 1.2037 | 4.62 | 2800 | 6.4232 | |
|
| 1.2037 | 4.79 | 2900 | 7.4486 | |
|
| 0.8386 | 4.95 | 3000 | 7.1946 | |
|
| 0.8386 | 5.12 | 3100 | 7.9869 | |
|
| 0.8386 | 5.28 | 3200 | 8.0310 | |
|
| 0.8386 | 5.45 | 3300 | 8.2954 | |
|
| 0.8386 | 5.61 | 3400 | 8.5361 | |
|
| 0.4389 | 5.78 | 3500 | 8.6040 | |
|
| 0.4389 | 5.94 | 3600 | 8.5806 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.15.0 |
|
- Pytorch 1.8.0+cu101 |
|
- Datasets 1.17.0 |
|
- Tokenizers 0.10.3 |
|
|
