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README.md ADDED
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+ ---
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+ base_model: ISTA-DASLab/Meta-Llama-3-8B-Instruct-AQLM-2Bit-1x16
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+ datasets:
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+ - red_pajama-data-1_t-sample
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+ library_name: peft
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: Meta-Llama-3-8B-Instruct-AQLM-2Bit-1x16-r8_bs4
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+ results: []
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # Meta-Llama-3-8B-Instruct-AQLM-2Bit-1x16-r8_bs4
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+
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+ This model is a fine-tuned version of [ISTA-DASLab/Meta-Llama-3-8B-Instruct-AQLM-2Bit-1x16](https://huggingface.co/ISTA-DASLab/Meta-Llama-3-8B-Instruct-AQLM-2Bit-1x16) on the red_pajama-data-1_t-sample dataset.
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 0.0002
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+ - train_batch_size: 4
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+ - eval_batch_size: 8
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+ - seed: 42
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+ - gradient_accumulation_steps: 16
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+ - total_train_batch_size: 64
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: linear
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+ - lr_scheduler_warmup_steps: 200
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+ - training_steps: 50000
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+
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+ ### Framework versions
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+
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+ - PEFT 0.11.1
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+ - Transformers 4.40.1
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+ - Pytorch 2.3.1
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+ - Datasets 2.19.0
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+ - Tokenizers 0.19.1
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+ "base_model_name_or_path": "ISTA-DASLab/Meta-Llama-3-8B-Instruct-AQLM-2Bit-1x16",
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+ "bias": "none",
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+ "fan_in_fan_out": false,
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+ "inference_mode": true,
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+ "init_lora_weights": true,
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+ "loftq_config": {},
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+ "lora_alpha": 8,
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+ "megatron_config": null,
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+ "megatron_core": "megatron.core",
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+ "modules_to_save": null,
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+ "peft_type": "LORA",
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+ "r": 8,
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+ "rank_pattern": {},
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+ "revision": null,
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+ "target_modules": [
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+ "q_proj",
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+ "v_proj",
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+ "gate_proj",
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+ "down_proj",
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+ "k_proj",
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+ "o_proj",
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+ "up_proj"
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+ ],
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+ "task_type": "CAUSAL_LM",
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+ "use_dora": false,
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+ "use_rslora": true
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+ }
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