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  ---
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  license: mit
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- library_name: "trl"
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  tags:
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- - KTO
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- - WeniGPT
 
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  base_model: HuggingFaceH4/zephyr-7b-beta
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  model-index:
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- - name: Weni/WeniGPT-Agents-Zephyr-1.0.9-KTO
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  results: []
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- language: ['pt']
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  ---
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- # Weni/WeniGPT-Agents-Zephyr-1.0.9-KTO
 
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- This model is a fine-tuned version of [HuggingFaceH4/zephyr-7b-beta] on the dataset Weni/wenigpt-agent-1.2.0 with the KTO trainer. It is part of the WeniGPT project for [Weni](https://weni.ai/).
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- Description: Hyperparameter search, altering desired and undesired weights for KTO task.
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  It achieves the following results on the evaluation set:
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- {'eval_loss': 0.5443353056907654, 'eval_runtime': 138.5128, 'eval_samples_per_second': 2.166, 'eval_steps_per_second': 0.541, 'eval_rewards/chosen': -130.8164825439453, 'eval_logps/chosen': -1605.7635498046875, 'eval_rewards/rejected': -121.00863647460938, 'eval_logps/rejected': -1472.8948974609375, 'eval_kl': 0.0, 'eval_rewards/margins': -16.295190811157227, 'epoch': 0.99}
 
 
 
 
 
 
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- ## Intended uses & limitations
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-
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- This model has not been trained to avoid specific intructions.
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-
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- ## Training procedure
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-
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- Finetuning was done on the model HuggingFaceH4/zephyr-7b-beta with the following prompt:
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-
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- ```
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- ---------------------
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- System_prompt:
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- Agora você se chama {name}, você é {occupation} e seu objetivo é {chatbot_goal}. O adjetivo que mais define a sua personalidade é {adjective} e você se comporta da seguinte forma:
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- {instructions_formatted}
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-
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- Na sua memória você tem esse contexto:
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- {context}
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- Lista de requisitos:
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- - Responda de forma natural, mas nunca fale sobre um assunto fora do contexto.
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- - Nunca traga informações do seu próprio conhecimento.
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- - Repito é crucial que você responda usando apenas informações do contexto.
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- - Nunca mencione o contexto fornecido.
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- - Nunca mencione a pergunta fornecida.
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- - Gere a resposta mais útil possível para a pergunta usando informações do conexto acima.
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- - Nunca elabore sobre o porque e como você fez a tarefa, apenas responda.
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-
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-
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- ---------------------
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- Question:
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- {question}
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- ---------------------
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- Response:
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- {answer}
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- ---------------------
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- ```
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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  - learning_rate: 0.0002
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- - per_device_train_batch_size: 4
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- - per_device_eval_batch_size: 4
 
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  - gradient_accumulation_steps: 4
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- - num_gpus: 1
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  - total_train_batch_size: 16
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- - optimizer: AdamW
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- - lr_scheduler_type: cosine
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- - num_steps: 145
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- - quantization_type: bitsandbytes
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- - LoRA: ("\n - bits: 4\n - use_exllama: True\n - device_map: auto\n - use_cache: False\n - lora_r: 16\n - lora_alpha: 32\n - lora_dropout: 0.05\n - bias: none\n - target_modules: ['q_proj', 'k_proj', 'v_proj', 'o_proj']\n - task_type: CAUSAL_LM",)
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  ### Training results
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  ### Framework versions
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- - transformers==4.39.1
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- - datasets==2.18.0
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- - peft==0.10.0
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- - safetensors==0.4.2
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- - evaluate==0.4.1
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- - bitsandbytes==0.43
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- - huggingface_hub==0.20.3
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- - seqeval==1.2.2
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- - optimum==1.17.1
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- - auto-gptq==0.7.1
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- - gpustat==1.1.1
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- - deepspeed==0.14.0
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- - wandb==0.16.3
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- - # trl==0.8.1
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- - git+https://github.com/kawine/trl.git#egg=trl
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- - accelerate==0.28.0
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- - coloredlogs==15.0.1
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- - traitlets==5.14.1
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- - autoawq@https://github.com/casper-hansen/AutoAWQ/releases/download/v0.2.0/autoawq-0.2.0+cu118-cp310-cp310-linux_x86_64.whl
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-
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- ### Hardware
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- - Cloud provided: runpod.io
 
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  ---
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  license: mit
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+ library_name: peft
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  tags:
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+ - trl
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+ - kto
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+ - generated_from_trainer
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  base_model: HuggingFaceH4/zephyr-7b-beta
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  model-index:
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+ - name: WeniGPT-Agents-Zephyr-1.0.9-KTO
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  results: []
 
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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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+ # WeniGPT-Agents-Zephyr-1.0.9-KTO
 
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+ This model is a fine-tuned version of [HuggingFaceH4/zephyr-7b-beta](https://huggingface.co/HuggingFaceH4/zephyr-7b-beta) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.5443
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+ - Rewards/chosen: -157.2410
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+ - Logps/chosen: -1859.8108
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+ - Rewards/rejected: -156.3582
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+ - Logps/rejected: -1831.8481
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+ - Kl: 0.0
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+ - Rewards/margins: 2.0475
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+ ## Model description
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ More information needed
 
 
 
 
 
 
 
 
 
 
 
 
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+ ## Intended uses & limitations
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+ More information needed
 
 
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+ ## Training and evaluation data
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+ More information needed
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+ ## Training procedure
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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  - learning_rate: 0.0002
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+ - train_batch_size: 4
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+ - eval_batch_size: 4
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+ - seed: 42
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  - gradient_accumulation_steps: 4
 
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  - total_train_batch_size: 16
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: linear
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+ - lr_scheduler_warmup_ratio: 0.03
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+ - training_steps: 145
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+ - mixed_precision_training: Native AMP
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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Logps/chosen | Rewards/rejected | Logps/rejected | Kl | Rewards/margins |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------------:|:------------:|:----------------:|:--------------:|:---:|:---------------:|
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+ | 0.5606 | 0.34 | 50 | 0.5443 | -151.0505 | -1797.9062 | -151.0357 | -1778.6233 | 0.0 | 2.7896 |
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+ | 0.4995 | 0.68 | 100 | 0.5443 | -157.2410 | -1859.8108 | -156.3582 | -1831.8481 | 0.0 | 2.0475 |
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+
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+
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  ### Framework versions
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+ - PEFT 0.10.0
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+ - Transformers 4.39.1
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+ - Pytorch 2.1.0+cu118
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+ - Datasets 2.18.0
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+ - Tokenizers 0.15.2