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Model Details

Model Description

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Model Sources [optional]

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Uses

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Out-of-Scope Use

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Bias, Risks, and Limitations

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Recommendations

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How to Get Started with the Model

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Training Details

Training Data

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Training Procedure

Preprocessing [optional]

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Training Hyperparameters

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llamafactory-cli train
--stage sft
--do_train True
--model_name_or_path Qwen/Qwen1.5-7B-Chat
--preprocessing_num_workers 16
--finetuning_type lora
--template qwen
--flash_attn auto
--dataset_dir data
--dataset healthcare
--cutoff_len 512
--learning_rate 0.0002
--num_train_epochs 1.0
--max_samples 10000
--per_device_train_batch_size 2
--gradient_accumulation_steps 16
--lr_scheduler_type cosine
--max_grad_norm 1.0
--logging_steps 5
--save_steps 100
--warmup_steps 0
--optim adamw_torch
--packing False
--report_to none
--output_dir saves/Qwen1.5-7B-Chat/lora/none-quantization_Qwen1.5-7B-Chat
--fp16 True
--plot_loss True
--ddp_timeout 180000000
--include_num_input_tokens_seen True
--lora_rank 16
--lora_alpha 16
--lora_dropout 0.05
--lora_target all \

Speeds, Sizes, Times [optional]

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Evaluation

Testing Data, Factors & Metrics

Testing Data

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Metrics

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Results

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Summary

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Environmental Impact

Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).

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Technical Specifications [optional]

Model Architecture and Objective

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