File size: 2,340 Bytes
696a561 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 |
---
base_model: vinai/phobert-base-v2
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: metadata-cls-gemini
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. -->
[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/nguyenducbao/huggingface/runs/08pk0u8k)
# metadata-cls-gemini
This model is a fine-tuned version of [vinai/phobert-base-v2](https://huggingface.co/vinai/phobert-base-v2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0111
- Accuracy: 0.8183
- F1: 0.7722
## 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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|:-------------:|:-------:|:----:|:---------------:|:--------:|:------:|
| 0.9411 | 1.6949 | 200 | 0.5887 | 0.8002 | 0.6394 |
| 0.4312 | 3.3898 | 400 | 0.5675 | 0.8097 | 0.7790 |
| 0.2745 | 5.0847 | 600 | 0.5685 | 0.8164 | 0.7767 |
| 0.2199 | 6.7797 | 800 | 0.6602 | 0.8116 | 0.7998 |
| 0.1536 | 8.4746 | 1000 | 0.8254 | 0.8069 | 0.7707 |
| 0.1021 | 10.1695 | 1200 | 0.8674 | 0.8097 | 0.7889 |
| 0.0928 | 11.8644 | 1400 | 0.8696 | 0.8145 | 0.7789 |
| 0.0692 | 13.5593 | 1600 | 0.9211 | 0.8259 | 0.7926 |
| 0.049 | 15.2542 | 1800 | 0.9573 | 0.8221 | 0.7899 |
| 0.0391 | 16.9492 | 2000 | 1.0388 | 0.8154 | 0.7713 |
| 0.0372 | 18.6441 | 2200 | 1.0111 | 0.8183 | 0.7722 |
### Framework versions
- Transformers 4.42.4
- Pytorch 2.1.2
- Datasets 2.20.0
- Tokenizers 0.19.1
|