Update qwen2_7b_lora_sft_4bit.yaml

llama-factory/config/qwen2_7b_lora_sft_4bit.yaml

@@ -1,5 +1,5 @@
 ### model
-model_name_or_path: Qwen/Qwen2-7B-Instruct
+model_name_or_path: Qwen/Qwen2-7B
 
 ### method
 stage: sft
@@ -8,39 +8,39 @@ finetuning_type: lora
 lora_target: all
 quantization_bit: 4                     # use 4-bit QLoRA
 loraplus_lr_ratio: 16.0                 # use LoRA+ with lambda=16.0
-# use_unsloth: true                       # use UnslothAI's LoRA optimization for 2x faster training
+upcast_layernorm: true
 
 ### dataset
-dataset: alpaca_mac
-template: chatml
-cutoff_len: 1024
-max_samples: 50
+dataset: mgtv_train
+template: qwen
+cutoff_len: 4096
+max_samples: 25000
 overwrite_cache: true
 preprocessing_num_workers: 16
 
 ### output
-output_dir: /content/qwen2-7b/
-logging_steps: 10
-save_steps: 10
+output_dir: saves/qwen2_7b/lora/sft_4bit
+logging_steps: 562
+save_steps: 562
 plot_loss: true
 overwrite_output_dir: true
 # resume_from_checkpoint: true
 
 ### train
-per_device_train_batch_size: 1
+per_device_train_batch_size: 32
 gradient_accumulation_steps: 8
 learning_rate: 1.0e-4
-num_train_epochs: 6.0
+num_train_epochs: 3.0
 lr_scheduler_type: cosine
 warmup_ratio: 0.1
 bf16: true
 ddp_timeout: 180000000
 
 ### eval
-val_size: 0.02
+val_size: 0.1
 per_device_eval_batch_size: 1
 eval_strategy: steps
-eval_steps: 10
+eval_steps: 562
 
 report_to: wandb
-run_name: qwen2_7b_mac_colab # optional
+run_name: qwen2_7b # optional