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README.md
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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-1.0.0-SFT-merged
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model-index:
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- name: WeniGPT-Agents-Mistral-1.0.0-SFT-1.0.24-DPO
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results: []
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---
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should probably proofread and complete it, then remove this comment. -->
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This model is a fine-tuned version of [Weni/WeniGPT-Agents-Mistral-1.0.0-SFT-merged](https://huggingface.co/Weni/WeniGPT-Agents-Mistral-1.0.0-SFT-merged) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Rewards/chosen: 2.6355
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- Rewards/rejected: -2.9994
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- Rewards/accuracies: 1.0
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- Rewards/margins: 5.6349
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- Logps/rejected: -208.5043
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- Logps/chosen: -182.0274
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- Logits/rejected: -1.9468
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- Logits/chosen: -1.9320
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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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- 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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- 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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| 0.2964 | 0.9677 | 30 | 0.2501 | 0.8715 | -0.1377 | 0.8571 | 1.0092 | -194.1958 | -190.8475 | -1.9378 | -1.9222 |
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| 0.1148 | 1.9355 | 60 | 0.1113 | 1.6463 | -0.7092 | 0.8571 | 2.3555 | -197.0533 | -186.9734 | -1.9501 | -1.9340 |
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| 0.0655 | 2.9032 | 90 | 0.0471 | 2.1122 | -1.4811 | 1.0 | 3.5933 | -200.9131 | -184.6442 | -1.9616 | -1.9457 |
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| 0.0279 | 3.8710 | 120 | 0.0218 | 2.5857 | -2.3439 | 1.0 | 4.9296 | -205.2268 | -182.2766 | -1.9554 | -1.9401 |
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| 0.0103 | 4.8387 | 150 | 0.0117 | 2.6480 | -2.7158 | 1.0 | 5.3638 | -207.0864 | -181.9648 | -1.9533 | -1.9384 |
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| 0.0052 | 5.8065 | 180 | 0.0082 | 2.6355 | -2.9994 | 1.0 | 5.6349 | -208.5043 | -182.0274 | -1.9468 | -1.9320 |
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### Framework versions
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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-1.0.0-SFT-merged
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model-index:
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- name: Weni/WeniGPT-Agents-Mistral-1.0.0-SFT-1.0.24-DPO
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results: []
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language: ['pt']
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---
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# Weni/WeniGPT-Agents-Mistral-1.0.0-SFT-1.0.24-DPO
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This model is a fine-tuned version of [Weni/WeniGPT-Agents-Mistral-1.0.0-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': 0.008221210911870003, 'eval_runtime': 15.9054, 'eval_samples_per_second': 1.76, 'eval_steps_per_second': 0.44, 'eval_rewards/chosen': 2.6355252265930176, 'eval_rewards/rejected': -2.999356508255005, 'eval_rewards/accuracies': 1.0, 'eval_rewards/margins': 5.634881496429443, 'eval_logps/rejected': -208.50425720214844, 'eval_logps/chosen': -182.0274200439453, 'eval_logits/rejected': -1.9468201398849487, 'eval_logits/chosen': -1.9320443868637085, '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-1.0.0-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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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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### 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: 64\n - lora_alpha: 32\n - lora_dropout: 0.05\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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### Hardware
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- Cloud provided: runpod.io
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