video_llava_qlora
This model is a fine-tuned version of LanguageBind/Video-LLaVA-7B-hf on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 7.3407
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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
8.3513 | 0.8989 | 10 | 8.2297 |
7.5778 | 1.7978 | 20 | 7.5320 |
7.3263 | 2.6966 | 30 | 7.3407 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.2.0+cu118
- Datasets 3.0.0
- Tokenizers 0.19.1
Training procedure
The following bitsandbytes
quantization config was used during training:
- quant_method: bitsandbytes
- _load_in_8bit: False
- _load_in_4bit: True
- llm_int8_threshold: 6.0
- llm_int8_skip_modules: None
- llm_int8_enable_fp32_cpu_offload: False
- llm_int8_has_fp16_weight: False
- bnb_4bit_quant_type: nf4
- bnb_4bit_use_double_quant: False
- bnb_4bit_compute_dtype: float16
- bnb_4bit_quant_storage: uint8
- load_in_4bit: True
- load_in_8bit: False
Framework versions
- PEFT 0.6.0
- Downloads last month
- 3
Inference Providers
NEW
This model isn't deployed by any Inference Provider.
๐
Ask for provider support
Model tree for NattawatW/video_llava_qlora
Base model
LanguageBind/Video-LLaVA-7B-hf