Downloads · 30 days
12
25% of all-time downloads
PhoBert_Dataset59KBoDuoi
RonTon05/PhoBert_Dataset59KBoDuoi
PhoBert_Dataset59KBoDuoi is a text classification model from RonTon05. Use it when you need a label for a piece of text. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
All-time downloads
48
Public
Parameters
135M
1.1 GB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors540 MB · 100%
At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- roberta
- Access
- Public
- Created
- Jun 22, 2024
- Updated
- Jun 22, 2024
- SHA
- 11104b29
Try a prompt
Base models
Model card
From the Hugging Face model README
<!-- 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. -->
PhoBert_Dataset59KBoDuoi
This model is a fine-tuned version of vinai/phobert-base-v2 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3898
- Accuracy: 0.8943
- F1: 0.8949
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: 128
- eval_batch_size: 128
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 256
- 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 |
|---|---|---|---|---|---|
| No log | 1.0230 | 200 | 0.3239 | 0.8676 | 0.8657 |
| No log | 2.0460 | 400 | 0.2895 | 0.8761 | 0.8750 |
| No log | 3.0691 | 600 | 0.2810 | 0.8862 | 0.8865 |
| 0.2918 | 4.0921 | 800 | 0.2887 | 0.8842 | 0.8856 |
| 0.2918 | 5.1151 | 1000 | 0.2770 | 0.8938 | 0.8945 |
| 0.2918 | 6.1381 | 1200 | 0.3323 | 0.8837 | 0.8856 |
| 0.2918 | 7.1611 | 1400 | 0.3013 | 0.8935 | 0.8942 |
| 0.1744 | 8.1841 | 1600 | 0.3146 | 0.8919 | 0.8935 |
| 0.1744 | 9.2072 | 1800 | 0.3165 | 0.8977 | 0.8978 |
| 0.1744 | 10.2302 | 2000 | 0.3452 | 0.8889 | 0.8903 |
| 0.1744 | 11.2532 | 2200 | 0.3487 | 0.8956 | 0.8964 |
| 0.1208 | 12.2762 | 2400 | 0.3420 | 0.8956 | 0.8963 |
| 0.1208 | 13.2992 | 2600 | 0.3441 | 0.8983 | 0.8984 |
| 0.1208 | 14.3223 | 2800 | 0.3713 | 0.8962 | 0.8966 |
| 0.1208 | 15.3453 | 3000 | 0.3696 | 0.8962 | 0.8968 |
| 0.0881 | 16.3683 | 3200 | 0.3812 | 0.8957 | 0.8964 |
| 0.0881 | 17.3913 | 3400 | 0.3824 | 0.8952 | 0.8958 |
| 0.0881 | 18.4143 | 3600 | 0.3838 | 0.8975 | 0.8978 |
| 0.0881 | 19.4373 | 3800 | 0.3898 | 0.8943 | 0.8949 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.19.2
- Tokenizers 0.19.1
- Task
- Text Classification
- Library
- transformers
- Type
- roberta
- Created
- Jun 22, 2024
- Updated
- Jun 22, 2024