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| import os |
| os.environ["HF_HUB_DISABLE_XET"] = "1" |
|
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| import trackio |
| from datasets import load_dataset |
| from peft import LoraConfig |
| from trl import SFTTrainer, SFTConfig |
|
|
| print("Loading memory-agent-sft-v1 dataset...") |
| dataset = load_dataset("erik1988/memory-agent-sft-v1", split="train") |
| print(f"Dataset loaded: {len(dataset)} examples") |
|
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| print(f"Train: {len(dataset)} examples (no eval split to save GPU memory)") |
|
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| config = SFTConfig( |
| output_dir="elias-memory-agent-v2", |
| push_to_hub=True, |
| hub_model_id="erik1988/elias-memory-agent-v2", |
| hub_strategy="every_save", |
| num_train_epochs=3, |
| per_device_train_batch_size=1, |
| gradient_accumulation_steps=8, |
| learning_rate=2e-5, |
| fp16=True, |
| max_length=512, |
| logging_steps=5, |
| save_strategy="steps", |
| save_steps=50, |
| save_total_limit=2, |
| warmup_ratio=0.1, |
| lr_scheduler_type="cosine", |
| gradient_checkpointing=True, |
| report_to="trackio", |
| project="elias-identity", |
| run_name="memory-agent-sft-v2-retry", |
| ) |
|
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| peft_config = LoraConfig( |
| r=16, |
| lora_alpha=32, |
| lora_dropout=0.05, |
| bias="none", |
| task_type="CAUSAL_LM", |
| target_modules=["q_proj", "v_proj"], |
| ) |
|
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| print("Initializing trainer with Qwen2.5-3B...") |
| trainer = SFTTrainer( |
| model="Qwen/Qwen2.5-3B", |
| train_dataset=dataset, |
| args=config, |
| peft_config=peft_config, |
| ) |
|
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| print("Starting training...") |
| trainer.train() |
| print("Pushing to Hub...") |
| trainer.push_to_hub() |
| trackio.finish() |
| print("DONE: Memory Agent v2") |
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