mirror of
https://github.com/hiyouga/LLaMA-Factory.git
synced 2025-12-16 11:50:35 +08:00
[misc] fix packing and eval plot (#7623)
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@@ -16,6 +16,7 @@ cutoff_len: 2048
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max_samples: 1000
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overwrite_cache: true
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preprocessing_num_workers: 16
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dataloader_num_workers: 4
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### output
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output_dir: saves/llama3-8b/lora/sft
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@@ -23,6 +24,8 @@ logging_steps: 10
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save_steps: 500
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plot_loss: true
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overwrite_output_dir: true
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save_only_model: false
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report_to: none # choices: [none, wandb, tensorboard, swanlab, mlflow]
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### train
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per_device_train_batch_size: 1
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@@ -16,6 +16,7 @@ cutoff_len: 2048
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max_samples: 1000
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overwrite_cache: true
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preprocessing_num_workers: 16
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dataloader_num_workers: 4
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### output
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output_dir: saves/llama3-8b/lora/sft
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@@ -23,6 +24,8 @@ logging_steps: 10
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save_steps: 500
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plot_loss: true
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overwrite_output_dir: true
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save_only_model: false
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report_to: none # choices: [none, wandb, tensorboard, swanlab, mlflow]
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### train
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per_device_train_batch_size: 1
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@@ -1,7 +1,7 @@
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### model
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model_name_or_path: meta-llama/Meta-Llama-3-8B-Instruct
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quantization_bit: 4
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quantization_method: bitsandbytes
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quantization_method: bnb
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double_quantization: false
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trust_remote_code: true
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@@ -19,6 +19,7 @@ cutoff_len: 2048
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max_samples: 1000
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overwrite_cache: true
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preprocessing_num_workers: 16
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dataloader_num_workers: 4
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### output
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output_dir: saves/llama3-8b/lora/sft
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@@ -26,6 +27,8 @@ logging_steps: 10
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save_steps: 500
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plot_loss: true
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overwrite_output_dir: true
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save_only_model: false
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report_to: none # choices: [none, wandb, tensorboard, swanlab, mlflow]
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### train
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per_device_train_batch_size: 1
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@@ -16,6 +16,7 @@ cutoff_len: 2048
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max_samples: 1000
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overwrite_cache: true
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preprocessing_num_workers: 16
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dataloader_num_workers: 4
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### output
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output_dir: saves/llama3-8b/lora/sft
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@@ -23,6 +24,8 @@ logging_steps: 10
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save_steps: 500
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plot_loss: true
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overwrite_output_dir: true
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save_only_model: false
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report_to: none # choices: [none, wandb, tensorboard, swanlab, mlflow]
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### train
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per_device_train_batch_size: 1
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@@ -1,7 +1,7 @@
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### model
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model_name_or_path: meta-llama/Meta-Llama-3-8B-Instruct
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quantization_bit: 4
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quantization_method: bitsandbytes # choices: [bitsandbytes (4/8), hqq (2/3/4/5/6/8), eetq (8)]
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quantization_bit: 4 # choices: [8 (bnb/hqq/eetq), 4 (bnb/hqq), 3 (hqq), 2 (hqq)]
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quantization_method: bnb # choices: [bnb, hqq, eetq]
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trust_remote_code: true
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### method
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@@ -18,6 +18,7 @@ cutoff_len: 2048
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max_samples: 1000
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overwrite_cache: true
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preprocessing_num_workers: 16
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dataloader_num_workers: 4
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### output
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output_dir: saves/llama3-8b/lora/sft
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@@ -25,6 +26,8 @@ logging_steps: 10
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save_steps: 500
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plot_loss: true
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overwrite_output_dir: true
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save_only_model: false
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report_to: none # choices: [none, wandb, tensorboard, swanlab, mlflow]
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### train
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per_device_train_batch_size: 1
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