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---
base_model: vinai/phobert-base
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: project-2-training-top
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. -->
# project-2-training-top
This model is a fine-tuned version of [vinai/phobert-base](https://huggingface.co/vinai/phobert-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3225
- F1: 0.6026
- Roc Auc: 0.7302
- Accuracy: 0.4977
## 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: 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: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy |
|:-------------:|:-----:|:------:|:---------------:|:------:|:-------:|:--------:|
| 0.3397 | 1.0 | 73895 | 0.3244 | 0.5931 | 0.7238 | 0.4826 |
| 0.337 | 2.0 | 147790 | 0.3232 | 0.5987 | 0.7277 | 0.4925 |
| 0.3448 | 3.0 | 221685 | 0.3225 | 0.6026 | 0.7302 | 0.4977 |
### Framework versions
- Transformers 4.38.2
- Pytorch 2.1.2
- Datasets 2.1.0
- Tokenizers 0.15.2
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