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vietcuna-3b_1024
duyvt6663/vietcuna-3b_1024
vietcuna-3b_1024 is a machine learning model from duyvt6663. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
should probably proofread and complete it, then remove this comment. --
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Public
Updated Nov 9, 2023
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At a glance
- Access
- Public
- Created
- Oct 24, 2023
- Updated
- Nov 9, 2023
- SHA
- 7e3b1ccc
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. -->
vietcuna-3b_2048
This model was trained from scratch on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5250
- Accuracy: 0.7375
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: 5e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.18
- training_steps: 1000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.5694 | 1.05 | 50 | 0.5834 | 0.7087 |
| 0.5614 | 2.1 | 100 | 0.5772 | 0.7165 |
| 0.5475 | 3.15 | 150 | 0.5684 | 0.7165 |
| 0.5503 | 4.2 | 200 | 0.5605 | 0.7087 |
| 0.5305 | 5.25 | 250 | 0.5784 | 0.7192 |
| 0.5353 | 6.3 | 300 | 0.5451 | 0.7323 |
| 0.5063 | 7.35 | 350 | 0.5441 | 0.7270 |
| 0.5141 | 8.4 | 400 | 0.5365 | 0.7244 |
| 0.5035 | 9.45 | 450 | 0.5354 | 0.7297 |
| 0.493 | 10.5 | 500 | 0.5322 | 0.7297 |
| 0.4763 | 11.55 | 550 | 0.5299 | 0.7375 |
| 0.5063 | 12.6 | 600 | 0.5295 | 0.7375 |
| 0.4787 | 13.65 | 650 | 0.5280 | 0.7297 |
| 0.4841 | 14.7 | 700 | 0.5266 | 0.7375 |
| 0.4732 | 15.75 | 750 | 0.5283 | 0.7297 |
| 0.4801 | 16.8 | 800 | 0.5259 | 0.7375 |
| 0.4651 | 17.85 | 850 | 0.5256 | 0.7375 |
| 0.4726 | 18.9 | 900 | 0.5260 | 0.7323 |
| 0.4758 | 19.95 | 950 | 0.5248 | 0.7375 |
| 0.4701 | 21.0 | 1000 | 0.5250 | 0.7375 |
Framework versions
- Transformers 4.35.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.14.6
- Tokenizers 0.14.1
- Created
- Oct 24, 2023
- Updated
- Nov 9, 2023