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llava_13b_exact_location_name
emendes3/llava_13b_exact_location_name
llava_13b_exact_location_name is a machine learning model from emendes3. 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.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- peft
- Model type
- llava_llama
- Access
- Public
- Created
- May 2, 2024
- Updated
- May 3, 2024
- SHA
- 4ca6d16f
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. -->
llava_13b_exact_location_name
This model is a fine-tuned version of liuhaotian/llava-v1.5-13b on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.4214
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: 0.0002
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- total_train_batch_size: 32
- total_eval_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 10.0
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.895 | 1.0 | 9 | 1.0173 |
| 0.2263 | 2.0 | 18 | 1.1246 |
| 0.0698 | 3.0 | 27 | 1.1885 |
| 0.0285 | 4.0 | 36 | 1.3967 |
| 0.0085 | 5.0 | 45 | 1.4823 |
| 0.0062 | 6.0 | 54 | 1.4699 |
| 0.0027 | 7.0 | 63 | 1.4972 |
| 0.0033 | 8.0 | 72 | 1.5496 |
| 0.0016 | 9.0 | 81 | 1.4242 |
| 0.0037 | 10.0 | 90 | 1.4214 |
Framework versions
- PEFT 0.10.0
- Transformers 4.37.2
- Pytorch 2.1.2+cu121
- Tokenizers 0.15.1
- Library
- peft
- Type
- llava_llama
- Created
- May 2, 2024
- Updated
- May 3, 2024