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Upload Qwen2ForCausalLM
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---
license: apache-2.0
metrics:
- bleu
tags:
- medical
- llama-factory
---
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
This modelcard aims to be a base template for new models. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/modelcard_template.md?plain=1).
## Model Details
### Model Description
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## Uses
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### Direct Use
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### Downstream Use [optional]
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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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Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
## How to Get Started with the Model
Use the code below to get started with the model.
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## Training Details
### Training Data
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### Training Procedure
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#### Preprocessing [optional]
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#### Training Hyperparameters
- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
llamafactory-cli train \
--stage sft \
--do_train True \
--model_name_or_path Qwen/Qwen1.5-7B-Chat \
--preprocessing_num_workers 16 \
--finetuning_type lora \
--quantization_bit 8 \
--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/8-bit_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
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### Testing Data, Factors & Metrics
#### Testing Data
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#### Factors
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#### Metrics
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### Results
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#### Summary
## Model Examination [optional]
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## Environmental Impact
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Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
- **Hardware Type:** [More Information Needed]
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## Technical Specifications [optional]
### Model Architecture and Objective
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### Compute Infrastructure
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#### Hardware
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#### Software
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## Citation [optional]
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**APA:**
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## Glossary [optional]
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