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---
library_name: transformers
license: mit
base_model: vinai/phobert-large
tags:
- generated_from_trainer
model-index:
- name: grab-ner-ghtk-ai-fluent-segmented-21-label-new-data-3090-6Obt-1
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. -->
# grab-ner-ghtk-ai-fluent-segmented-21-label-new-data-3090-6Obt-1
This model is a fine-tuned version of [vinai/phobert-large](https://huggingface.co/vinai/phobert-large) on the None dataset.
## 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: 2.5e-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: 1
### Training results
| Training Loss | Epoch | Step | Validation Loss | Ho | Hoảng thời gian | Háng trừu tượng | Hông tin ctt | Hụ cấp | Hứ | Iấy tờ | Iền cụ thể | Iền trừu tượng | Ã số thuế | Ã đơn | Ình thức làm việc | Ông | Ương | Ị trí | Ố công | Ố giờ | Ố điểm | Ố đơn | Ợt | Ỷ lệ | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------------------------------------------------------:|:---------------------------------------------------------:|:----------------------------------------------------------:|:---------------------------------------------------------:|:-------------------------------------------------------------------------------------------------------:|:---------------------------------------------------------:|:---------------------------------------------------------:|:----------------------------------------------------------:|:---------------------------------------------------------:|:---------------------------------------------------------:|:----------------------------------------------------------:|:---------------------------------------------------------:|:---------------------------------------------------------------------------------------------------------:|:----------------------------------------------------------:|:----------------------------------------------------------:|:--------------------------------------------------------------------------------------------------------:|:---------------------------------------------------------:|:----------------------------------------------------------:|:----------------------------------------------------------:|:---------------------------------------------------------:|:---------------------------------------------------------:|:-----------------:|:--------------:|:----------:|:----------------:|
| No log | 1.0 | 147 | 0.4119 | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 3} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 5} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 10} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 6} | {'precision': 0.5657894736842105, 'recall': 0.6825396825396826, 'f1': 0.6187050359712231, 'number': 63} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 9} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 8} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 31} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 5} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 2} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 22} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 2} | {'precision': 0.26865671641791045, 'recall': 0.43902439024390244, 'f1': 0.3333333333333333, 'number': 82} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 54} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 16} | {'precision': 0.6808510638297872, 'recall': 0.9411764705882353, 'f1': 0.7901234567901235, 'number': 238} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 4} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 42} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 17} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 3} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1} | 0.5622 | 0.4864 | 0.5215 | 0.8912 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1
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