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README.md
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- llama
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- trl
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- sft
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---
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# Uploaded model
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This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
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[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
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- llama
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- trl
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- sft
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datasets:
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- emessy/flash_fiction_1
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---
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# Uploaded model
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This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
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[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
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# Configure LoRA
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lora_config = LoraConfig(
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r=16,
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lora_alpha=16,
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target_modules=["q_proj", "k_proj", "v_proj", "o_proj"],
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lora_dropout=0.05,
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bias="none",
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task_type="CAUSAL_LM"
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)
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# Training arguments
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training_args = TrainingArguments(
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output_dir="./results",
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num_train_epochs=5,
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per_device_train_batch_size=4,
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gradient_accumulation_steps=4,
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learning_rate=2e-4,
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fp16=True, # Use half-precision
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logging_steps=10,
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save_steps=50,
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eval_steps=50,
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)
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