|
--- |
|
base_model: HooshvareLab/bert-base-parsbert-uncased |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- precision |
|
- recall |
|
- accuracy |
|
model-index: |
|
- name: output |
|
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. --> |
|
|
|
# output |
|
|
|
This model is a fine-tuned version of [HooshvareLab/bert-base-parsbert-uncased](https://huggingface.co/HooshvareLab/bert-base-parsbert-uncased) on the None dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.2551 |
|
- Precision: 0.9362 |
|
- Recall: 0.9360 |
|
- Fscore: 0.9359 |
|
- Accuracy: 0.9360 |
|
|
|
## 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: 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: 10 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | Fscore | Accuracy | |
|
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
|
| No log | 1.0 | 348 | 0.3054 | 0.9166 | 0.9144 | 0.9136 | 0.9144 | |
|
| 0.5158 | 2.0 | 696 | 0.2551 | 0.9362 | 0.9360 | 0.9359 | 0.9360 | |
|
| 0.1469 | 3.0 | 1044 | 0.3670 | 0.9283 | 0.9259 | 0.9245 | 0.9259 | |
|
| 0.1469 | 4.0 | 1392 | 0.3833 | 0.9331 | 0.9317 | 0.9307 | 0.9317 | |
|
| 0.0453 | 5.0 | 1740 | 0.4241 | 0.9356 | 0.9345 | 0.9342 | 0.9345 | |
|
| 0.0237 | 6.0 | 2088 | 0.3750 | 0.9441 | 0.9439 | 0.9437 | 0.9439 | |
|
| 0.0237 | 7.0 | 2436 | 0.3986 | 0.9389 | 0.9388 | 0.9385 | 0.9388 | |
|
| 0.009 | 8.0 | 2784 | 0.4100 | 0.9407 | 0.9403 | 0.9397 | 0.9403 | |
|
| 0.0053 | 9.0 | 3132 | 0.4005 | 0.9403 | 0.9403 | 0.9401 | 0.9403 | |
|
| 0.0053 | 10.0 | 3480 | 0.3986 | 0.9410 | 0.9410 | 0.9408 | 0.9410 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.33.1 |
|
- Pytorch 2.0.1+cu118 |
|
- Datasets 2.14.5 |
|
- Tokenizers 0.13.3 |
|
|