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When I finetune llama7b:
# alpaca torchrun --nproc_per_node=8 --master_port=29000 train.py \ --model_name_or_path .cache/hub/models--meta-llama--Llama-2-7b-hf/snapshots/01c7f73d771dfac7d292323805ebc428287df4f9 \ --data_path ./alpaca_data.json \ --bf16 True \ --output_dir output/Llama-2-7b-hf \ --num_train_epochs 3 \ --per_device_train_batch_size 2 \ --per_device_eval_batch_size 4 \ --gradient_accumulation_steps 8 \ --evaluation_strategy "no" \ --save_strategy "epoch" \ --save_steps 2000 \ --save_total_limit 1 \ --learning_rate 2e-5 \ --weight_decay 0. \ --warmup_ratio 0.03 \ --lr_scheduler_type "cosine" \ --logging_steps 1 \ --fsdp "full_shard auto_wrap" \ --fsdp_transformer_layer_cls_to_wrap 'LlamaDecoderLayer' \ --tf32 True \ --model_max_length 512 ;
then load by transformers:
ValueError: Trying to set a tensor of shape torch.Size([32769536]) in "weight" (which has shape torch.Size([32001, 4096])), this looks incorrect.
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I met the same situation.
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how about downgrade Accelerate to 0.30.0?
I finally sovle this err by upgrading python from 3.9->3.10,without downgrading accelerate.
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When I finetune llama7b:
then load by transformers:
The text was updated successfully, but these errors were encountered: