|
--- |
|
license: apache-2.0 |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- precision |
|
- recall |
|
- f1 |
|
- accuracy |
|
model-index: |
|
- name: finetuned_parsBERT_NER_fa |
|
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. --> |
|
|
|
# finetuned_parsBERT_NER_fa |
|
|
|
This model is a fine-tuned version of [HooshvareLab/bert-fa-zwnj-base](https://huggingface.co/HooshvareLab/bert-fa-zwnj-base) on the mixed NER dataset collected from ARMAN, PEYMA, and WikiANN. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.0297 |
|
- Precision: 0.9481 |
|
- Recall: 0.9582 |
|
- F1: 0.9531 |
|
- Accuracy: 0.9942 |
|
|
|
## 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: 16 |
|
- eval_batch_size: 16 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- num_epochs: 5 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
|
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
|
| 0.12 | 1.0 | 1821 | 0.0543 | 0.8387 | 0.8577 | 0.8481 | 0.9830 | |
|
| 0.0381 | 2.0 | 3642 | 0.0360 | 0.8941 | 0.9247 | 0.9091 | 0.9898 | |
|
| 0.0168 | 3.0 | 5463 | 0.0282 | 0.9273 | 0.9452 | 0.9362 | 0.9927 | |
|
| 0.0078 | 4.0 | 7284 | 0.0284 | 0.9391 | 0.9551 | 0.9470 | 0.9938 | |
|
| 0.0033 | 5.0 | 9105 | 0.0297 | 0.9481 | 0.9582 | 0.9531 | 0.9942 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.21.2 |
|
- Pytorch 1.12.1+cu113 |
|
- Datasets 2.4.0 |
|
- Tokenizers 0.12.1 |
|
|
