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23_128_e3_3e-5/README.md ADDED
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+ ---
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+ library_name: peft
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+ license: apache-2.0
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+ base_model: ibm-granite/granite-3.3-8b-base
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+ tags:
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+ - alignment-handbook
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+ - generated_from_trainer
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+ datasets:
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+ - data/knowledge_lora_training_data_2000
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+ model-index:
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+ - name: 23_128_e3_3e-5
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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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+ # 23_128_e3_3e-5
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+
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+ This model is a fine-tuned version of [ibm-granite/granite-3.3-8b-base](https://huggingface.co/ibm-granite/granite-3.3-8b-base) on the data/knowledge_lora_training_data_2000 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: 3e-05
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+ - train_batch_size: 2
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+ - eval_batch_size: 8
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+ - seed: 42
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+ - distributed_type: multi-GPU
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+ - num_devices: 8
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+ - gradient_accumulation_steps: 2
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+ - total_train_batch_size: 32
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+ - total_eval_batch_size: 64
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+ - optimizer: Use adamw_torch with betas=(0.9,0.95) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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+ - lr_scheduler_type: cosine
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+ - lr_scheduler_warmup_ratio: 0.05
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+ - num_epochs: 3.0
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+
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+ ### Training results
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+
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+
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+
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+ ### Framework versions
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+
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+ - PEFT 0.15.2
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+ - Transformers 4.52.4
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+ - Pytorch 2.7.0+cu126
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+ - Datasets 3.6.0
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+ - Tokenizers 0.21.2
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+ "init_lora_weights": true,
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+ "megatron_core": "megatron.core",
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+ "peft_type": "LORA",
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+ "r": 128,
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+ "target_modules": [
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+ ],
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+ "task_type": "CAUSAL_LM",
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+ "trainable_token_indices": null,
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+ "use_dora": false,
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+ "use_rslora": false
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+ }
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