File size: 2,425 Bytes
90dcf06 |
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 74 |
---
base_model: vinai/phobert-base-v2
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: metadata-cls-no-gov-8k-v3
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/gi7dm5g5)
# metadata-cls-no-gov-8k-v3
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: 0.3064
- Accuracy: 0.9515
- F1: 0.8155
## 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 |
|:-------------:|:-------:|:----:|:---------------:|:--------:|:------:|
| 0.5565 | 1.6393 | 200 | 0.1942 | 0.9472 | 0.7911 |
| 0.1619 | 3.2787 | 400 | 0.1935 | 0.9404 | 0.7817 |
| 0.1275 | 4.9180 | 600 | 0.1903 | 0.9430 | 0.8019 |
| 0.0768 | 6.5574 | 800 | 0.2192 | 0.9489 | 0.8016 |
| 0.0579 | 8.1967 | 1000 | 0.2350 | 0.9455 | 0.7866 |
| 0.0477 | 9.8361 | 1200 | 0.2572 | 0.9498 | 0.7952 |
| 0.0358 | 11.4754 | 1400 | 0.2823 | 0.9413 | 0.7938 |
| 0.0277 | 13.1148 | 1600 | 0.2704 | 0.9464 | 0.8096 |
| 0.0233 | 14.7541 | 1800 | 0.2868 | 0.9481 | 0.7951 |
| 0.0139 | 16.3934 | 2000 | 0.3026 | 0.9438 | 0.7965 |
| 0.0125 | 18.0328 | 2200 | 0.3034 | 0.9489 | 0.8035 |
| 0.0085 | 19.6721 | 2400 | 0.3064 | 0.9515 | 0.8155 |
### Framework versions
- Transformers 4.42.4
- Pytorch 2.1.2
- Datasets 2.20.0
- Tokenizers 0.19.1
|