|
--- |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- precision |
|
- recall |
|
- f1 |
|
- accuracy |
|
model-index: |
|
- name: layoutlmv3-er-ner |
|
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. --> |
|
|
|
# layoutlmv3-er-ner |
|
|
|
This model is a fine-tuned version of [renjithks/layoutlmv3-cord-ner](https://huggingface.co/renjithks/layoutlmv3-cord-ner) on an unknown dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.2025 |
|
- Precision: 0.6442 |
|
- Recall: 0.6761 |
|
- F1: 0.6598 |
|
- Accuracy: 0.9507 |
|
|
|
## 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: 8 |
|
- eval_batch_size: 8 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- num_epochs: 10 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
|
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
|
| No log | 1.0 | 22 | 0.2940 | 0.4214 | 0.2956 | 0.3475 | 0.9147 | |
|
| No log | 2.0 | 44 | 0.2487 | 0.4134 | 0.4526 | 0.4321 | 0.9175 | |
|
| No log | 3.0 | 66 | 0.1922 | 0.5399 | 0.5460 | 0.5429 | 0.9392 | |
|
| No log | 4.0 | 88 | 0.1977 | 0.5653 | 0.5813 | 0.5732 | 0.9434 | |
|
| No log | 5.0 | 110 | 0.2018 | 0.6173 | 0.6252 | 0.6212 | 0.9477 | |
|
| No log | 6.0 | 132 | 0.1823 | 0.6232 | 0.6153 | 0.6192 | 0.9485 | |
|
| No log | 7.0 | 154 | 0.1972 | 0.6203 | 0.6238 | 0.6220 | 0.9477 | |
|
| No log | 8.0 | 176 | 0.1952 | 0.6292 | 0.6407 | 0.6349 | 0.9511 | |
|
| No log | 9.0 | 198 | 0.2070 | 0.6331 | 0.6492 | 0.6411 | 0.9489 | |
|
| No log | 10.0 | 220 | 0.2025 | 0.6442 | 0.6761 | 0.6598 | 0.9507 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.20.0.dev0 |
|
- Pytorch 1.11.0 |
|
- Datasets 2.1.0 |
|
- Tokenizers 0.12.1 |
|
|
