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gemma4-e2b-webvid4K_FT – AI Model by bear7011 | AlphaNeural AI
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gemma4-e2b-webvid4K_FT
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transformers
safetensors
gemma4
image-text-to-text
conversational
endpoints_compatible
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gemma4-e2b-webvid4K_FT
Full fine-tune of
google/gemma-4-e2b-it
on AI-generated video data derived from WebVid.
Training
Dataset:
bear7011/gemma-4-e4b-webvid-4K
Samples: 3,941 video instruction examples
Method: full fine-tuning, no LoRA
Precision: bfloat16
GPUs: 4
DeepSpeed: ZeRO-3 with CPU optimizer and parameter offload
Epochs: 1
Global steps: 124
Per-device batch size: 1
Gradient accumulation steps: 8
Optimizer: AdamW
Learning rate: 5e-6
Projector learning rate: 5e-6
Image encoder learning rate: 0.0
Weight decay: 0.01
Warmup ratio: 0.03
LR scheduler: cosine
Gradient checkpointing: enabled
Max sequence length: 2304
Final training loss: 1.9510 Checkpoints and training logs are not included in this repository.
