Model save

README.md

@@ -1,84 +1,70 @@
 ---
 license: mit
-library_name: "trl"
+library_name: peft
 tags:
-- DPO
-- WeniGPT
-base_model: Weni/WeniGPT-2.3.3-Zephyr-7B-zephyr-prompt-LLM_Base_2.0.3_SFT_reduction_variation
+- trl
+- dpo
+- generated_from_trainer
+base_model: HuggingFaceH4/zephyr-7b-beta
 model-index:
-- name: Weni/WeniGPT-DPO-test
+- name: WeniGPT-DPO-test
   results: []
-language: ['pt']
 ---
 
-# Weni/WeniGPT-DPO-test
+<!-- 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. -->
 
-This model is a fine-tuned version of [Weni/WeniGPT-2.3.3-Zephyr-7B-zephyr-prompt-LLM_Base_2.0.3_SFT_reduction_variation] on the dataset Weni/WeniGPT-QA-1.0.1_DPO with the DPO trainer. It is part of the WeniGPT project for [Weni](https://weni.ai/).
+# WeniGPT-DPO-test
 
+This model is a fine-tuned version of [HuggingFaceH4/zephyr-7b-beta](https://huggingface.co/HuggingFaceH4/zephyr-7b-beta) on an unknown dataset.
 It achieves the following results on the evaluation set:
-{'eval_loss': 0.6931471228599548, 'eval_runtime': 213.9537, 'eval_samples_per_second': 1.486, 'eval_steps_per_second': 0.743, 'eval_rewards/chosen': 0.0, 'eval_rewards/rejected': 0.0, 'eval_rewards/accuracies': 0.0, 'eval_rewards/margins': 0.0, 'eval_logps/rejected': -12.07151985168457, 'eval_logps/chosen': -7.126925468444824, 'eval_logits/rejected': -2.2169549465179443, 'eval_logits/chosen': -2.2155022621154785, 'epoch': 0.0}
+- Loss: 0.6931
+- Rewards/chosen: 0.0
+- Rewards/rejected: 0.0
+- Rewards/accuracies: 0.0
+- Rewards/margins: 0.0
+- Logps/rejected: -12.7530
+- Logps/chosen: -7.2418
+- Logits/rejected: -2.2130
+- Logits/chosen: -2.2118
 
-## Intended uses & limitations
+## Model description
 
-This model has not been trained to avoid specific intructions. 
+More information needed
 
-## Training procedure
+## Intended uses & limitations
 
-Finetuning was done on the model Weni/WeniGPT-2.3.3-Zephyr-7B-zephyr-prompt-LLM_Base_2.0.3_SFT_reduction_variation with the following prompt:
+More information needed
 
-```
-Pt:
-	### Instruction:
-Você é um médico tratando um paciente com amnésia. Para responder as perguntas do paciente, você irá ler um texto anteriormente para se contextualizar. Se você trouxer informações desconhecidas, fora do texto lido, poderá deixar o paciente confuso. Se o paciente fizer uma questão sobre informações não presentes no texto, você precisa responder de forma educada que você não tem informação suficiente para responder, pois se tentar responder, pode trazer informações que não ajudarão o paciente recuperar sua memória.Lembre, se não estiver no texto, você precisa responder de forma educada que você não tem informação suficiente para responder. Precisamos ajudar o paciente.
-</s>### Input:
-TEXTO: {context}
+## Training and evaluation data
 
-PERGUNTA: {question}
-</s>
-	### Response:
-RESPOSTA: {chosen_response}</s>
-	### Response:
-RESPOSTA: {rejected_response}</s>
+More information needed
 
-```
+## Training procedure
 
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
 - learning_rate: 2e-05
-- per_device_train_batch_size: 2
-- per_device_eval_batch_size: 2
+- train_batch_size: 2
+- eval_batch_size: 2
+- seed: 42
 - gradient_accumulation_steps: 2
-- num_gpus: 1
 - total_train_batch_size: 4
-- optimizer: AdamW
-- lr_scheduler_type: cosine
-- num_steps: 1
-- 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: 0.1\n  - bias: none\n  - target_modules: ['q_proj', 'k_proj', 'v_proj', 'o_proj']\n  - task_type: CAUSAL_LM",)
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- training_steps: 1
+- mixed_precision_training: Native AMP
 
 ### Training results
 
+
+
 ### Framework versions
 
-- transformers==4.38.2
-- datasets==2.17.1
-- peft==0.8.2
-- safetensors==0.4.2
-- evaluate==0.4.1
-- bitsandbytes==0.42
-- huggingface_hub==0.20.3
-- seqeval==1.2.2
-- optimum==1.17.1
-- auto-gptq==0.7.0
-- gpustat==1.1.1
-- deepspeed==0.13.2
-- wandb==0.16.3
-- trl==0.7.11
-- accelerate==0.27.2
-- coloredlogs==15.0.1
-- traitlets==5.14.1
-- autoawq@https://github.com/casper-hansen/AutoAWQ/releases/download/v0.2.0/autoawq-0.2.0+cu118-cp310-cp310-linux_x86_64.whl
-
-### Hardware
-- Cloud provided: runpod.io
+- PEFT 0.8.2
+- Transformers 4.38.2
+- Pytorch 2.1.0+cu118
+- Datasets 2.17.1
+- Tokenizers 0.15.1

adapter_config.json

@@ -19,10 +19,10 @@
   "rank_pattern": {},
   "revision": null,
   "target_modules": [
+    "q_proj",
     "k_proj",
     "v_proj",
-    "o_proj",
-    "q_proj"
+    "o_proj"
   ],
   "task_type": "CAUSAL_LM",
   "use_rslora": false

adapter_model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:9bbef180681f144aae4e266886f413c0f6b6c0936912eabd09a8897ae9acbdc2
+oid sha256:68fed0784d71b880f07f58c125f95587e8591c55910f9e9e8db3bc44019974bf
 size 27297032

training_args.bin

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:ce8377191e16f6eb828ceffe2c170ab150349bf2b9a967e1cf197dfafb511f61
+oid sha256:456c5c5b03a026d5e2a70a799231d8f2b2d00e4a08eec9014824ff0300f8482e
 size 5112