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Update llama.py

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Daniel Han 2025-03-14 01:18:04 -07:00
commit 7ccacc3faf
1 changed files with 6 additions and 1 deletions
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unsloth/models/llama.py
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@ -1883,12 +1883,17 @@ class FastLlamaModel:
f" {chr(92)}{chr(92)} /| Num examples = {num_examples:,} | Num Epochs = {num_train_epochs:,} | Total steps = {max_steps:,}\\n"\\
f"O^O/ {chr(92)}_/ {chr(92)} Batch size per device = {self._train_batch_size:,} | Gradient accumulation steps = {args.gradient_accumulation_steps}\\n"\\
f"{chr(92)} / Data Parallel GPUs = {args.world_size} | Total batch size ({self._train_batch_size} x {args.gradient_accumulation_steps} x {args.world_size}) = {total_train_batch_size:,}\\n"\\
f' "-____-" Trainable parameters = {get_model_param_count(model, trainable_only=True):,}/{get_model_param_count(model):,} ({get_model_param_count(model, trainable_only=True)/get_model_param_count(model)*100:.2f}% trained)'
f' "-____-" Trainable parameters = {P__(model, trainable_only=True):,}/{P__(model)*multiplier__:,} ({P__(model, trainable_only=True)/(P__(model)*multiplier__)*100:.2f}% trained)'
logger.warning(debug_info)
import gc
for _ in range(3):
gc.collect()
torch.cuda.empty_cache()"""
multiplier = \
"4.5 if getattr(model.config, 'quantization_config', {'load_in_4bit' : False})['load_in_4bit'] else "\
"8.0 if getattr(model.config, 'quantization_config', {'load_in_8bit' : False})['load_in_8bit'] else 1.0"
debug_info = debug_info.replace("multiplier__", "(" + multiplier + ")")
debug_info = debug_info.replace("P__", "get_model_param_count")
debug_info = debug_info.split('\n')
debug_info = "\n".join([debug_info[0]] + [spaces + x[8:] for x in debug_info[1:]])