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A10-Llasa-1B_220K
zhcheng/A10-Llasa-1B_220K
A10-Llasa-1B_220K is a machine learning model from zhcheng. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for peft. The card lists the license as cc-by-nc-4.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- peft
- License
- cc-by-nc-4.0
- Access
- Public
- Created
- May 31, 2025
- Updated
- May 31, 2025
- SHA
- 1040485f
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. -->
A10-Llasa-1B_220K
This model is a fine-tuned version of HKUSTAudio/Llasa-1B on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 7.3216
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: 3
- eval_batch_size: 3
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 4
- total_train_batch_size: 24
- total_eval_batch_size: 6
- optimizer: Adam with betas=(0.9,0.95) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 1
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 0 | 0 | 7.8117 |
| 7.3694 | 0.0089 | 1000 | 7.5275 |
| 7.3694 | 0.0089 | 1000 | 7.5158 |
| 7.0835 | 0.0715 | 2000 | 7.4015 |
| 7.0793 | 0.1072 | 3000 | 7.3785 |
| 7.0461 | 0.1430 | 4000 | 7.3690 |
| 7.0339 | 0.1787 | 5000 | 7.3580 |
| 6.9696 | 0.2144 | 6000 | 7.3513 |
| 7.033 | 0.2502 | 7000 | 7.3444 |
| 6.9768 | 0.2859 | 8000 | 7.3387 |
| 7.1218 | 0.3216 | 9000 | 7.3378 |
| 7.041 | 0.3574 | 10000 | 7.3314 |
| 6.9799 | 0.3931 | 11000 | 7.3350 |
| 7.0261 | 0.4289 | 12000 | 7.3297 |
| 6.888 | 0.4646 | 13000 | 7.3288 |
| 6.9483 | 0.5003 | 14000 | 7.3285 |
| 6.989 | 0.5361 | 15000 | 7.3269 |
| 7.0167 | 0.5718 | 16000 | 7.3243 |
| 6.9611 | 0.6076 | 17000 | 7.3273 |
| 6.9077 | 0.6433 | 18000 | 7.3256 |
| 7.0845 | 0.6790 | 19000 | 7.3235 |
| 6.8593 | 0.7148 | 20000 | 7.3207 |
| 6.8621 | 0.7505 | 21000 | 7.3216 |
| 7.1707 | 0.7863 | 22000 | 7.3225 |
| 6.9153 | 0.8220 | 23000 | 7.3209 |
| 6.9139 | 0.8577 | 24000 | 7.3217 |
| 6.9 | 0.8935 | 25000 | 7.3214 |
| 6.7397 | 0.9292 | 26000 | 7.3207 |
| 6.9967 | 0.9649 | 27000 | 7.3216 |
Framework versions
- PEFT 0.15.2
- Transformers 4.45.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.1
- Library
- peft
- License
- cc-by-nc-4.0
- Created
- May 31, 2025
- Updated
- May 31, 2025