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output – AI Model by Shaoni | AlphaNeural AI
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peft
safetensors
generated_from_trainer
vq_av2
google/paligemma-3b-pt-224
adapter
gemma
us
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output
This model is a fine-tuned version of
google/paligemma-3b-pt-224
on the vq_av2 dataset.
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: 2e-05
train_batch_size: 16
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 64
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 2
num_epochs: 1
Training results
Framework versions
Transformers 4.42.0.dev0
Pytorch 2.1.1+cu121
Datasets 2.14.5
Tokenizers 0.19.1
Training procedure
The following
bitsandbytes
quantization config was used during training:
quant_method: QuantizationMethod.BITS_AND_BYTES
_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: float32
bnb_4bit_quant_storage: uint8
load_in_4bit: True
load_in_8bit: False
Framework versions
PEFT 0.6.2
