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---
base_model: vinai/phobert-base
tags:
- generated_from_trainer
model-index:
- name: CS505-Classifier-T4_predictLabel_a1_v2
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. -->
# CS505-Classifier-T4_predictLabel_a1_v2
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: 0.0077
## 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: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 25
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| No log | 0.98 | 48 | 1.0151 |
| No log | 1.96 | 96 | 0.5423 |
| No log | 2.94 | 144 | 0.3287 |
| No log | 3.92 | 192 | 0.2296 |
| No log | 4.9 | 240 | 0.1795 |
| No log | 5.88 | 288 | 0.1419 |
| No log | 6.86 | 336 | 0.1083 |
| No log | 7.84 | 384 | 0.0807 |
| No log | 8.82 | 432 | 0.0609 |
| No log | 9.8 | 480 | 0.0614 |
| 0.3965 | 10.78 | 528 | 0.0349 |
| 0.3965 | 11.76 | 576 | 0.0289 |
| 0.3965 | 12.73 | 624 | 0.0252 |
| 0.3965 | 13.71 | 672 | 0.0193 |
| 0.3965 | 14.69 | 720 | 0.0163 |
| 0.3965 | 15.67 | 768 | 0.0147 |
| 0.3965 | 16.65 | 816 | 0.0139 |
| 0.3965 | 17.63 | 864 | 0.0134 |
| 0.3965 | 18.61 | 912 | 0.0114 |
| 0.3965 | 19.59 | 960 | 0.0100 |
| 0.0339 | 20.57 | 1008 | 0.0083 |
| 0.0339 | 21.55 | 1056 | 0.0079 |
| 0.0339 | 22.53 | 1104 | 0.0077 |
| 0.0339 | 23.51 | 1152 | 0.0081 |
| 0.0339 | 24.49 | 1200 | 0.0077 |
### Framework versions
- Transformers 4.38.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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