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  ---
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- library_name: peft
 
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  tags:
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- - trl
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- - dpo
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  - DPO
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  - WeniGPT
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- - generated_from_trainer
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  base_model: Weni/WeniGPT-Agents-Mistral-1.0.6-SFT-merged
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  model-index:
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- - name: WeniGPT-Agents-Mistral-1.0.6-SFT-1.0.12-DPO
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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-Mistral-1.0.6-SFT-1.0.12-DPO
 
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- This model is a fine-tuned version of [Weni/WeniGPT-Agents-Mistral-1.0.6-SFT-merged](https://huggingface.co/Weni/WeniGPT-Agents-Mistral-1.0.6-SFT-merged) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0136
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- - Rewards/chosen: 4.0493
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- - Rewards/rejected: -5.6491
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- - Rewards/accuracies: 1.0
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- - Rewards/margins: 9.6984
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- - Logps/rejected: -289.7536
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- - Logps/chosen: -114.5970
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- - Logits/rejected: -1.7999
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- - Logits/chosen: -1.6729
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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: 5e-06
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- - train_batch_size: 1
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- - eval_batch_size: 1
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- - seed: 42
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- - distributed_type: multi-GPU
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- - num_devices: 4
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  - gradient_accumulation_steps: 2
 
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  - total_train_batch_size: 8
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- - total_eval_batch_size: 4
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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: 180
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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 | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
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- |:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
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- | 0.3146 | 0.9677 | 30 | 0.2348 | 2.4895 | -0.9698 | 1.0 | 3.4593 | -274.1559 | -119.7963 | -1.8004 | -1.6854 |
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- | 0.1205 | 1.9355 | 60 | 0.1243 | 3.2997 | -1.8481 | 1.0 | 5.1477 | -277.0835 | -117.0959 | -1.8004 | -1.6813 |
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- | 0.0546 | 2.9032 | 90 | 0.0516 | 3.7979 | -3.0261 | 1.0 | 6.8240 | -281.0103 | -115.4352 | -1.8019 | -1.6787 |
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- | 0.0314 | 3.8710 | 120 | 0.0325 | 4.0534 | -4.3569 | 1.0 | 8.4102 | -285.4462 | -114.5836 | -1.8025 | -1.6771 |
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- | 0.0298 | 4.8387 | 150 | 0.0160 | 4.0881 | -5.2113 | 1.0 | 9.2994 | -288.2944 | -114.4678 | -1.8015 | -1.6752 |
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- | 0.0156 | 5.8065 | 180 | 0.0136 | 4.0493 | -5.6491 | 1.0 | 9.6984 | -289.7536 | -114.5970 | -1.7999 | -1.6729 |
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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 4.40.0
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- - Pytorch 2.1.0+cu118
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- - Datasets 2.18.0
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- - Tokenizers 0.19.1
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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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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  - DPO
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  - WeniGPT
 
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  base_model: Weni/WeniGPT-Agents-Mistral-1.0.6-SFT-merged
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  model-index:
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+ - name: Weni/WeniGPT-Agents-Mistral-1.0.6-SFT-1.0.12-DPO
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  results: []
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+ language: ['pt']
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  ---
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+ # Weni/WeniGPT-Agents-Mistral-1.0.6-SFT-1.0.12-DPO
 
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+ This model is a fine-tuned version of [Weni/WeniGPT-Agents-Mistral-1.0.6-SFT-merged] on the dataset Weni/wenigpt-agent-dpo-1.0.0 with the DPO trainer. It is part of the WeniGPT project for [Weni](https://weni.ai/).
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+ Description: Experiment on DPO with other hyperparameters and best SFT model of WeniGPT
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  It achieves the following results on the evaluation set:
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+ {'eval_loss': 0.013596544042229652, 'eval_runtime': 9.818, 'eval_samples_per_second': 2.852, 'eval_steps_per_second': 0.713, 'eval_rewards/chosen': 4.049325466156006, 'eval_rewards/rejected': -5.6490702629089355, 'eval_rewards/accuracies': 1.0, 'eval_rewards/margins': 9.698395729064941, 'eval_logps/rejected': -289.7535705566406, 'eval_logps/chosen': -114.59700012207031, 'eval_logits/rejected': -1.7999308109283447, 'eval_logits/chosen': -1.6729296445846558, 'epoch': 5.806451612903226}
 
 
 
 
 
 
 
 
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+ ## Intended uses & limitations
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+ This model has not been trained to avoid specific intructions.
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+ ## Training procedure
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+ Finetuning was done on the model Weni/WeniGPT-Agents-Mistral-1.0.6-SFT-merged with the following prompt:
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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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+ {context_statement}
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+
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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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+ ```
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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  - learning_rate: 5e-06
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+ - per_device_train_batch_size: 1
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+ - per_device_eval_batch_size: 1
 
 
 
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  - gradient_accumulation_steps: 2
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+ - num_gpus: 4
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  - total_train_batch_size: 8
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+ - optimizer: AdamW
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+ - lr_scheduler_type: cosine
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+ - num_steps: 180
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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: 8\n - lora_alpha: 16\n - lora_dropout: 0.1\n - bias: none\n - target_modules: ['q_proj', 'k_proj', 'v_proj', 'o_proj', 'gate_proj', 'up_proj', 'down_proj']\n - task_type: CAUSAL_LM",)
 
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  ### Training results
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  ### Framework versions
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+ - transformers==4.40.0
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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==0.22.2
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+ - seqeval==1.2.2
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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==0.16.6
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+ - trl==0.8.1
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+ - accelerate==0.29.3
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+ - coloredlogs==15.0.1
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+ - traitlets==5.14.2
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+ - git+https://github.com/casper-hansen/AutoAWQ.git
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+
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+ ### Hardware
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+ - Cloud provided: runpod.io