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README.md

@@ -1,88 +1,90 @@
 ---
-library_name: peft
+license: mit
+library_name: "trl"
 tags:
-- trl
-- dpo
 - DPO
 - WeniGPT
-- generated_from_trainer
 base_model: Weni/WeniGPT-Agents-Mistral-1.0.6-SFT-merged
 model-index:
-- name: WeniGPT-Agents-Mistral-1.0.6-SFT-1.0.11-DPO
+- name: Weni/WeniGPT-Agents-Mistral-1.0.6-SFT-1.0.11-DPO
   results: []
+language: ['pt']
 ---
 
-<!-- This model card has been generated automatically according to the information the Trainer had access to. You
-should probably proofread and complete it, then remove this comment. -->
+# Weni/WeniGPT-Agents-Mistral-1.0.6-SFT-1.0.11-DPO
 
-# WeniGPT-Agents-Mistral-1.0.6-SFT-1.0.11-DPO
+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/).
+Description: Experiment on DPO with other hyperparameters and best SFT model of WeniGPT
 
-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.
 It achieves the following results on the evaluation set:
-- Loss: 0.2882
-- Rewards/chosen: 1.1764
-- Rewards/rejected: -0.8691
-- Rewards/accuracies: 0.7857
-- Rewards/margins: 2.0455
-- Logps/rejected: -193.9308
-- Logps/chosen: -125.0071
-- Logits/rejected: -1.8155
-- Logits/chosen: -1.7656
+{'eval_loss': 0.2881975471973419, 'eval_runtime': 17.3794, 'eval_samples_per_second': 1.611, 'eval_steps_per_second': 0.806, 'eval_rewards/chosen': 1.1763746738433838, 'eval_rewards/rejected': -0.8690943121910095, 'eval_rewards/accuracies': 0.7857142686843872, 'eval_rewards/margins': 2.045469045639038, 'eval_logps/rejected': -193.93080139160156, 'eval_logps/chosen': -125.00711822509766, 'eval_logits/rejected': -1.8155311346054077, 'eval_logits/chosen': -1.7656012773513794, 'epoch': 5.951219512195122}
 
-## Model description
+## Intended uses & limitations
 
-More information needed
+This model has not been trained to avoid specific intructions. 
 
-## Intended uses & limitations
+## Training procedure
 
-More information needed
+Finetuning was done on the model Weni/WeniGPT-Agents-Mistral-1.0.6-SFT-merged with the following prompt:
 
-## Training and evaluation data
+```
+---------------------
+System_prompt:
+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:
+{instructions_formatted}
 
-More information needed
+{context_statement}
+
+Lista de requisitos:
+ - Responda de forma natural, mas nunca fale sobre um assunto fora do contexto.
+ - Nunca traga informações do seu próprio conhecimento.
+ - Repito é crucial que você responda usando apenas informações do contexto.
+ - Nunca mencione o contexto fornecido.
+ - Nunca mencione a pergunta fornecida.
+ - Gere a resposta mais útil possível para a pergunta usando informações do conexto acima.
+ - Nunca elabore sobre o porque e como você fez a tarefa, apenas responda.
 
-## Training procedure
+
+---------------------
+
+```
 
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
 - learning_rate: 5e-06
-- train_batch_size: 1
-- eval_batch_size: 1
-- seed: 42
-- distributed_type: multi-GPU
-- num_devices: 2
+- per_device_train_batch_size: 1
+- per_device_eval_batch_size: 1
 - gradient_accumulation_steps: 2
+- num_gpus: 2
 - total_train_batch_size: 4
-- total_eval_batch_size: 2
-- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
-- lr_scheduler_type: linear
-- lr_scheduler_warmup_ratio: 0.03
-- training_steps: 366
-- mixed_precision_training: Native AMP
+- optimizer: AdamW
+- lr_scheduler_type: cosine
+- num_steps: 366
+- quantization_type: bitsandbytes
+- 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: 0.05\n  - bias: none\n  - target_modules: ['v_proj', 'q_proj']\n  - task_type: CAUSAL_LM",)
 
 ### Training results
 
-| Training Loss | Epoch  | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
-|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
-| 0.6531        | 0.4878 | 30   | 0.6394          | 0.1271         | -0.0075          | 0.7857             | 0.1346          | -185.3151      | -135.4998    | -1.7717         | -1.7290       |
-| 0.5732        | 0.9756 | 60   | 0.5476          | 0.3645         | -0.0302          | 0.7857             | 0.3947          | -185.5418      | -133.1256    | -1.7778         | -1.7342       |
-| 0.5252        | 1.4634 | 90   | 0.4644          | 0.6021         | -0.0850          | 0.7857             | 0.6871          | -186.0897      | -130.7499    | -1.7853         | -1.7405       |
-| 0.4402        | 1.9512 | 120  | 0.4089          | 0.7788         | -0.1757          | 0.7857             | 0.9545          | -186.9970      | -128.9828    | -1.7949         | -1.7492       |
-| 0.4138        | 2.4390 | 150  | 0.3652          | 0.9271         | -0.3082          | 0.7857             | 1.2353          | -188.3218      | -127.4999    | -1.8014         | -1.7541       |
-| 0.3863        | 2.9268 | 180  | 0.3403          | 1.0288         | -0.4194          | 0.7857             | 1.4482          | -189.4338      | -126.4830    | -1.8065         | -1.7584       |
-| 0.2999        | 3.4146 | 210  | 0.3210          | 1.0940         | -0.5570          | 0.7857             | 1.6510          | -190.8097      | -125.8309    | -1.8114         | -1.7629       |
-| 0.2311        | 3.9024 | 240  | 0.3085          | 1.1291         | -0.6550          | 0.7857             | 1.7841          | -191.7899      | -125.4799    | -1.8136         | -1.7646       |
-| 0.2992        | 4.3902 | 270  | 0.3012          | 1.1494         | -0.7427          | 0.7857             | 1.8921          | -192.6667      | -125.2770    | -1.8147         | -1.7654       |
-| 0.2532        | 4.8780 | 300  | 0.2943          | 1.1602         | -0.8051          | 0.7857             | 1.9653          | -193.2910      | -125.1693    | -1.8146         | -1.7650       |
-| 0.2564        | 5.3659 | 330  | 0.2905          | 1.1717         | -0.8471          | 0.7857             | 2.0188          | -193.7112      | -125.0541    | -1.8151         | -1.7652       |
-| 0.2457        | 5.8537 | 360  | 0.2882          | 1.1764         | -0.8691          | 0.7857             | 2.0455          | -193.9308      | -125.0071    | -1.8155         | -1.7656       |
-
-
 ### Framework versions
 
-- PEFT 0.10.0
-- Transformers 4.40.0
-- Pytorch 2.1.0+cu118
-- Datasets 2.18.0
-- Tokenizers 0.19.1
+- transformers==4.40.0
+- datasets==2.18.0
+- peft==0.10.0
+- safetensors==0.4.2
+- evaluate==0.4.1
+- bitsandbytes==0.43
+- huggingface_hub==0.22.2
+- seqeval==1.2.2
+- auto-gptq==0.7.1
+- gpustat==1.1.1
+- deepspeed==0.14.0
+- wandb==0.16.6
+- trl==0.8.1
+- accelerate==0.29.3
+- coloredlogs==15.0.1
+- traitlets==5.14.2
+- git+https://github.com/casper-hansen/AutoAWQ.git
+
+### Hardware
+- Cloud provided: runpod.io