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  1. LLM-Detector-V3-11w/README.md +56 -0
  2. LLM-Detector-V3-11w/adapter_config.json +23 -0
  3. LLM-Detector-V3-11w/adapter_model.bin +3 -0
  4. LLM-Detector-V3-11w/all_results.json +7 -0
  5. LLM-Detector-V3-11w/checkpoint-10000/README.md +219 -0
  6. LLM-Detector-V3-11w/checkpoint-10000/adapter_config.json +23 -0
  7. LLM-Detector-V3-11w/checkpoint-10000/adapter_model.bin +3 -0
  8. LLM-Detector-V3-11w/checkpoint-10000/optimizer.pt +3 -0
  9. LLM-Detector-V3-11w/checkpoint-10000/rng_state.pth +3 -0
  10. LLM-Detector-V3-11w/checkpoint-10000/scheduler.pt +3 -0
  11. LLM-Detector-V3-11w/checkpoint-10000/special_tokens_map.json +24 -0
  12. LLM-Detector-V3-11w/checkpoint-10000/tokenizer.json +0 -0
  13. LLM-Detector-V3-11w/checkpoint-10000/tokenizer.model +3 -0
  14. LLM-Detector-V3-11w/checkpoint-10000/tokenizer_config.json +34 -0
  15. LLM-Detector-V3-11w/checkpoint-10000/trainer_state.json +619 -0
  16. LLM-Detector-V3-11w/checkpoint-10000/training_args.bin +3 -0
  17. LLM-Detector-V3-11w/checkpoint-5000/README.md +219 -0
  18. LLM-Detector-V3-11w/checkpoint-5000/adapter_config.json +23 -0
  19. LLM-Detector-V3-11w/checkpoint-5000/adapter_model.bin +3 -0
  20. LLM-Detector-V3-11w/checkpoint-5000/optimizer.pt +3 -0
  21. LLM-Detector-V3-11w/checkpoint-5000/rng_state.pth +3 -0
  22. LLM-Detector-V3-11w/checkpoint-5000/scheduler.pt +3 -0
  23. LLM-Detector-V3-11w/checkpoint-5000/special_tokens_map.json +24 -0
  24. LLM-Detector-V3-11w/checkpoint-5000/tokenizer.json +0 -0
  25. LLM-Detector-V3-11w/checkpoint-5000/tokenizer.model +3 -0
  26. LLM-Detector-V3-11w/checkpoint-5000/tokenizer_config.json +34 -0
  27. LLM-Detector-V3-11w/checkpoint-5000/trainer_state.json +319 -0
  28. LLM-Detector-V3-11w/checkpoint-5000/training_args.bin +3 -0
  29. LLM-Detector-V3-11w/special_tokens_map.json +24 -0
  30. LLM-Detector-V3-11w/tokenizer.json +0 -0
  31. LLM-Detector-V3-11w/tokenizer.model +3 -0
  32. LLM-Detector-V3-11w/tokenizer_config.json +34 -0
  33. LLM-Detector-V3-11w/train_results.json +7 -0
  34. LLM-Detector-V3-11w/trainer_log.jsonl +112 -0
  35. LLM-Detector-V3-11w/trainer_state.json +694 -0
  36. LLM-Detector-V3-11w/training_args.bin +3 -0
  37. LLM-Detector-V3-11w/training_loss.png +0 -0
LLM-Detector-V3-11w/README.md ADDED
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+ ---
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+ license: other
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+ base_model: ./llama-2-7b-chat-hf
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+ tags:
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+ - llama-factory
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+ - lora
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+ - generated_from_trainer
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+ model-index:
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+ - name: llama2-7b
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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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+ # llama2-7b
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+
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+ This model is a fine-tuned version of [./llama-2-7b-chat-hf](https://huggingface.co/./llama-2-7b-chat-hf) on the ta, the tb, the tc, the td, the te, the tf, the tg and the th datasets.
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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: 5e-05
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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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+ - 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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+ - Transformers 4.33.0
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+ - Pytorch 2.1.1+cu121
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+ - Datasets 2.14.7
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+ - Tokenizers 0.13.3
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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": "./llama-2-7b-chat-hf",
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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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+ "layers_pattern": null,
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+ "layers_to_transform": null,
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+ "lora_alpha": 16.0,
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+ "lora_dropout": 0.1,
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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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+ ],
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+ "task_type": "CAUSAL_LM"
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+ }
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+ {
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+ "epoch": 3.0,
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+ "train_loss": 0.03027582302646779,
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+ "train_runtime": 186831.816,
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+ "train_samples_per_second": 1.91,
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+ "train_steps_per_second": 0.06
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LLM-Detector-V3-11w/checkpoint-10000/README.md ADDED
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+ ---
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+ library_name: peft
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+ base_model: ./llama-2-7b-chat-hf
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+ ---
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+
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+ # Model Card for Model ID
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+
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+ <!-- Provide a quick summary of what the model is/does. -->
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+
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+
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+
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+ ## Model Details
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+
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+ ### Model Description
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+
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+ <!-- Provide a longer summary of what this model is. -->
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+
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+
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+
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+ - **Developed by:** [More Information Needed]
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+ - **Shared by [optional]:** [More Information Needed]
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+ - **Model type:** [More Information Needed]
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+ - **Language(s) (NLP):** [More Information Needed]
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+ - **License:** [More Information Needed]
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+ - **Finetuned from model [optional]:** [More Information Needed]
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+
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+ ### Model Sources [optional]
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+
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+ <!-- Provide the basic links for the model. -->
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+
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+ - **Repository:** [More Information Needed]
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+ - **Paper [optional]:** [More Information Needed]
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+ - **Demo [optional]:** [More Information Needed]
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+
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+ ## Uses
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+
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+ <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
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+
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+ ### Direct Use
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+
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+ <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
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+
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+ [More Information Needed]
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+
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+ ### Downstream Use [optional]
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+
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+ <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
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+
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+ [More Information Needed]
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+
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+ ### Out-of-Scope Use
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+
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+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
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+
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+ [More Information Needed]
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+
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+ ## Bias, Risks, and Limitations
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+
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+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
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+
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+ [More Information Needed]
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+
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+ ### Recommendations
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+
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+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
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+
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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.
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+
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+ ## How to Get Started with the Model
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+
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+ Use the code below to get started with the model.
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+
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+ [More Information Needed]
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+
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+ ## Training Details
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+
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+ ### Training Data
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+
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+ <!-- This should link to a Data Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
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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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+ <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
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+
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+ #### Preprocessing [optional]
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+
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+ [More Information Needed]
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+
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+
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+ #### Training Hyperparameters
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+
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+ - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
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+
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+ #### Speeds, Sizes, Times [optional]
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+
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+ <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
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+
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+ [More Information Needed]
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+
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+ ## Evaluation
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+
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+ <!-- This section describes the evaluation protocols and provides the results. -->
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+
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+ ### Testing Data, Factors & Metrics
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+
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+ #### Testing Data
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+
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+ <!-- This should link to a Data Card if possible. -->
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+
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+ [More Information Needed]
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+
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+ #### Factors
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+
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+ <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
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+
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+ [More Information Needed]
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+
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+ #### Metrics
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+
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+ <!-- These are the evaluation metrics being used, ideally with a description of why. -->
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+
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+ [More Information Needed]
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+
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+ ### Results
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+
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+ [More Information Needed]
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+
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+ #### Summary
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+
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+
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+
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+ ## Model Examination [optional]
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+
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+ <!-- Relevant interpretability work for the model goes here -->
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+
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+ [More Information Needed]
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+
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+ ## Environmental Impact
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+
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+ <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
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+
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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).
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+
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+ - **Hardware Type:** [More Information Needed]
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+ - **Hours used:** [More Information Needed]
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+ - **Cloud Provider:** [More Information Needed]
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+ - **Compute Region:** [More Information Needed]
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+ - **Carbon Emitted:** [More Information Needed]
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+
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+ ## Technical Specifications [optional]
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+
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+ ### Model Architecture and Objective
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+
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+ [More Information Needed]
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+
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+ ### Compute Infrastructure
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+
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+ [More Information Needed]
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+
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+ #### Hardware
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+
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+ [More Information Needed]
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+
166
+ #### Software
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+
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+ [More Information Needed]
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+
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+ ## Citation [optional]
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+
172
+ <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
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+
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+ **BibTeX:**
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+
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+ [More Information Needed]
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+
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+ **APA:**
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+
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+ [More Information Needed]
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+
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+ ## Glossary [optional]
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+
184
+ <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
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+
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+ [More Information Needed]
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+
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+ ## More Information [optional]
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+
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+ [More Information Needed]
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+
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+ ## Model Card Authors [optional]
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+
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+ [More Information Needed]
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+
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+ ## Model Card Contact
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+
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+ [More Information Needed]
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+
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+
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+ ## Training procedure
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+
203
+
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+ The following `bitsandbytes` quantization config was used during training:
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+ - quant_method: QuantizationMethod.BITS_AND_BYTES
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+ - load_in_8bit: False
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+ - load_in_4bit: True
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+ - llm_int8_threshold: 6.0
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+ - llm_int8_skip_modules: None
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+ - llm_int8_enable_fp32_cpu_offload: False
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+ - llm_int8_has_fp16_weight: False
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+ - bnb_4bit_quant_type: nf4
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+ - bnb_4bit_use_double_quant: True
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+ - bnb_4bit_compute_dtype: float16
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+
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+ ### Framework versions
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+
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+
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+ - PEFT 0.6.2
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+ }
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+ ---
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+ library_name: peft
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+ base_model: ./llama-2-7b-chat-hf
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+ ---
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+
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+ # Model Card for Model ID
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+
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+ <!-- Provide a quick summary of what the model is/does. -->
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+
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+
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+
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+ ## Model Details
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+
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+ ### Model Description
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+
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+ <!-- Provide a longer summary of what this model is. -->
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+
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+
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+
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+ - **Developed by:** [More Information Needed]
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+ - **Shared by [optional]:** [More Information Needed]
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+ ## Uses
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+ ### Direct Use
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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.
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+ ## How to Get Started with the Model
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+ #### Preprocessing [optional]
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+ ### Results
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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).
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+ ## Training procedure
202
+
203
+
204
+ The following `bitsandbytes` quantization config was used during training:
205
+ - quant_method: QuantizationMethod.BITS_AND_BYTES
206
+ - load_in_8bit: False
207
+ - load_in_4bit: True
208
+ - llm_int8_threshold: 6.0
209
+ - llm_int8_skip_modules: None
210
+ - llm_int8_enable_fp32_cpu_offload: False
211
+ - llm_int8_has_fp16_weight: False
212
+ - bnb_4bit_quant_type: nf4
213
+ - bnb_4bit_use_double_quant: True
214
+ - bnb_4bit_compute_dtype: float16
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+
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+ ### Framework versions
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+
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+
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+ - PEFT 0.6.2
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