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--- |
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library_name: peft |
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--- |
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## Dataset procedure |
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- GPT4-generated dataset |
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- size: 80 |
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- per_device_train_batch_size=4, |
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- gradient_accumulation_steps=4, |
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- warmup_steps=100, |
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- max_steps=200, |
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- learning_rate=2e-4, |
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- fp16=True, |
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- logging_steps=1, |
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- output_dir='outputs', |
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## Training procedure |
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The following `bitsandbytes` quantization config was used during training: |
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- quant_method: bitsandbytes |
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- load_in_8bit: True |
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- load_in_4bit: False |
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- llm_int8_threshold: 6.0 |
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- llm_int8_skip_modules: None |
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- llm_int8_enable_fp32_cpu_offload: False |
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- llm_int8_has_fp16_weight: False |
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- bnb_4bit_quant_type: fp4 |
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- bnb_4bit_use_double_quant: False |
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- bnb_4bit_compute_dtype: float32 |
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## LoraConfig procedure |
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r=16, #attention heads |
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lora_alpha=32, #alpha scaling |
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# target_modules=["q_proj", "v_proj"], #if you know the |
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lora_dropout=0.05, |
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bias="none", |
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task_type="CAUSAL_LM" # set this for CLM or Seq2Seq |
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### Framework versions |
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- PEFT 0.6.0.dev0 |
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