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README.md ADDED
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+ ---
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+ license: apache-2.0
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+ library_name: peft
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+ tags:
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+ - trl-sft
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+ - generated_from_trainer
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+ datasets:
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+ - wikisql
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+ base_model: TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T
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+ model-index:
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+ - name: tinyllama_lora_sql
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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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+ # tinyllama_lora_sql
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+
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+ This model is a fine-tuned version of [TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T](https://huggingface.co/TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T) on the wikisql dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.0562
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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: 0.0005
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+ - train_batch_size: 8
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+ - eval_batch_size: 8
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+ - seed: 42
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+ - gradient_accumulation_steps: 4
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+ - total_train_batch_size: 32
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: cosine
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+ - lr_scheduler_warmup_ratio: 0.1
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+ - num_epochs: 1
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+ - mixed_precision_training: Native AMP
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss |
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+ |:-------------:|:-----:|:----:|:---------------:|
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+ | 0.0664 | 1.0 | 263 | 0.0562 |
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+
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+
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+ ### Framework versions
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+
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+ - PEFT 0.7.2.dev0
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+ - Transformers 4.37.0.dev0
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+ - Pytorch 2.1.2+cu121
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+ - Datasets 2.15.0
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+ - Tokenizers 0.15.0
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+ {
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+ "alpha_pattern": {},
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+ "auto_mapping": null,
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+ "base_model_name_or_path": "TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T",
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+ "bias": "none",
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+ "inference_mode": true,
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+ "init_lora_weights": true,
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+ "peft_type": "LORA",
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+ "r": 8,
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+ "rank_pattern": {},
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+ "target_modules": [
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+ "gate_proj",
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+ ],
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+ "task_type": "CAUSAL_LM",
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+ "use_rslora": false
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+ }
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