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- checkpoint-180/README.md +202 -0
- checkpoint-180/adapter_config.json +29 -0
- checkpoint-180/adapter_model.safetensors +3 -0
- checkpoint-180/optimizer.pt +3 -0
- checkpoint-180/rng_state_0.pth +3 -0
- checkpoint-180/rng_state_1.pth +3 -0
- checkpoint-180/rng_state_2.pth +3 -0
- checkpoint-180/rng_state_3.pth +3 -0
- checkpoint-180/scheduler.pt +3 -0
- checkpoint-180/special_tokens_map.json +24 -0
- checkpoint-180/tokenizer.json +0 -0
- checkpoint-180/tokenizer.model +3 -0
- checkpoint-180/tokenizer_config.json +49 -0
- checkpoint-180/trainer_state.json +387 -0
- checkpoint-180/training_args.bin +3 -0
- checkpoint-90/README.md +202 -0
- checkpoint-90/adapter_config.json +29 -0
- checkpoint-90/adapter_model.safetensors +3 -0
- checkpoint-90/optimizer.pt +3 -0
- checkpoint-90/rng_state_0.pth +3 -0
- checkpoint-90/rng_state_1.pth +3 -0
- checkpoint-90/rng_state_2.pth +3 -0
- checkpoint-90/rng_state_3.pth +3 -0
- checkpoint-90/scheduler.pt +3 -0
- checkpoint-90/special_tokens_map.json +24 -0
- checkpoint-90/tokenizer.json +0 -0
- checkpoint-90/tokenizer.model +3 -0
- checkpoint-90/tokenizer_config.json +49 -0
- checkpoint-90/trainer_state.json +204 -0
- checkpoint-90/training_args.bin +3 -0
README.md
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---
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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-1.0.8-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-1.0.6-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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- Rewards/chosen: 1.7621
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- Rewards/rejected: -0.7248
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- Rewards/accuracies: 1.0
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- Rewards/margins: 2.4869
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- Logps/rejected: -271.5133
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- Logps/chosen: -102.9727
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- Logits/rejected: -1.8958
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- Logits/chosen: -1.8013
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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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| 0.5477 | 0.97 | 30 | 0.4843 | 0.4718 | -0.1109 | 0.8571 | 0.5827 | -269.4668 | -107.2735 | -1.8863 | -1.7949 |
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| 0.3542 | 1.94 | 60 | 0.3440 | 0.9609 | -0.2516 | 1.0 | 1.2125 | -269.9360 | -105.6431 | -1.8903 | -1.7979 |
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| 0.2892 | 2.9 | 90 | 0.2756 | 1.3199 | -0.4182 | 1.0 | 1.7381 | -270.4914 | -104.4467 | -1.8928 | -1.7995 |
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| 0.1858 | 3.87 | 120 | 0.2327 | 1.6010 | -0.5696 | 1.0 | 2.1706 | -270.9958 | -103.5094 | -1.8947 | -1.8008 |
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| 0.1811 | 4.84 | 150 | 0.2076 | 1.7245 | -0.6925 | 1.0 | 2.4170 | -271.4054 | -103.0979 | -1.8954 | -1.8010 |
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| 0.2065 | 5.81 | 180 | 0.2005 | 1.7621 | -0.7248 | 1.0 | 2.4869 | -271.5133 | -102.9727 | -1.8958 | -1.8013 |
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### Framework versions
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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-1.0.8-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-1.0.8-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': 0.20048503577709198, 'eval_runtime': 9.9205, 'eval_samples_per_second': 2.822, 'eval_steps_per_second': 0.706, 'eval_rewards/chosen': 1.7620631456375122, 'eval_rewards/rejected': -0.7248173952102661, 'eval_rewards/accuracies': 1.0, 'eval_rewards/margins': 2.4868807792663574, 'eval_logps/rejected': -271.5132751464844, 'eval_logps/chosen': -102.97270202636719, 'eval_logits/rejected': -1.8957865238189697, 'eval_logits/chosen': -1.8012962341308594, 'epoch': 5.81}
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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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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: 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",)
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### Training results
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### Framework versions
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- transformers==4.38.2
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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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- optimum==1.18.1
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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==0.16.6
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- trl==0.8.1
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- accelerate==0.29.2
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- coloredlogs==15.0.1
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- traitlets==5.14.2
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- autoawq@https://github.com/casper-hansen/AutoAWQ/releases/download/v0.2.4/autoawq-0.2.4+cu118-cp310-cp310-linux_x86_64.whl
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### Hardware
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- Cloud provided: runpod.io
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checkpoint-180/README.md
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---
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library_name: peft
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base_model: Weni/WeniGPT-Agents-Mistral-1.0.6-SFT-merged
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---
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# Model Card for Model ID
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<!-- Provide a quick summary of what the model is/does. -->
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## Model Details
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### Model Description
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<!-- Provide a longer summary of what this model is. -->
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- **Developed by:** [More Information Needed]
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- **Funded by [optional]:** [More Information Needed]
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- **Shared by [optional]:** [More Information Needed]
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- **Model type:** [More Information Needed]
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- **Language(s) (NLP):** [More Information Needed]
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- **License:** [More Information Needed]
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- **Finetuned from model [optional]:** [More Information Needed]
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### Model Sources [optional]
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- **Repository:** [More Information Needed]
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- **Paper [optional]:** [More Information Needed]
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- **Demo [optional]:** [More Information Needed]
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## Uses
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<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
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### Direct Use
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<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
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[More Information Needed]
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### Downstream Use [optional]
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<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
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[More Information Needed]
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### Out-of-Scope Use
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<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
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[More Information Needed]
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## Bias, Risks, and Limitations
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<!-- This section is meant to convey both technical and sociotechnical limitations. -->
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[More Information Needed]
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### Recommendations
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<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
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Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
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## How to Get Started with the Model
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Use the code below to get started with the model.
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[More Information Needed]
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## Training Details
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### Training Data
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<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
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[More Information Needed]
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### Training Procedure
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<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
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#### Preprocessing [optional]
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[More Information Needed]
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#### Training Hyperparameters
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- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
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#### Speeds, Sizes, Times [optional]
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<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
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[More Information Needed]
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## Evaluation
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<!-- This section describes the evaluation protocols and provides the results. -->
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### Testing Data, Factors & Metrics
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#### Testing Data
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[More Information Needed]
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#### Factors
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<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
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[More Information Needed]
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#### Metrics
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<!-- These are the evaluation metrics being used, ideally with a description of why. -->
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[More Information Needed]
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### Results
|
128 |
+
|
129 |
+
[More Information Needed]
|
130 |
+
|
131 |
+
#### Summary
|
132 |
+
|
133 |
+
|
134 |
+
|
135 |
+
## Model Examination [optional]
|
136 |
+
|
137 |
+
<!-- Relevant interpretability work for the model goes here -->
|
138 |
+
|
139 |
+
[More Information Needed]
|
140 |
+
|
141 |
+
## Environmental Impact
|
142 |
+
|
143 |
+
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
|
144 |
+
|
145 |
+
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
|
146 |
+
|
147 |
+
- **Hardware Type:** [More Information Needed]
|
148 |
+
- **Hours used:** [More Information Needed]
|
149 |
+
- **Cloud Provider:** [More Information Needed]
|
150 |
+
- **Compute Region:** [More Information Needed]
|
151 |
+
- **Carbon Emitted:** [More Information Needed]
|
152 |
+
|
153 |
+
## Technical Specifications [optional]
|
154 |
+
|
155 |
+
### Model Architecture and Objective
|
156 |
+
|
157 |
+
[More Information Needed]
|
158 |
+
|
159 |
+
### Compute Infrastructure
|
160 |
+
|
161 |
+
[More Information Needed]
|
162 |
+
|
163 |
+
#### Hardware
|
164 |
+
|
165 |
+
[More Information Needed]
|
166 |
+
|
167 |
+
#### Software
|
168 |
+
|
169 |
+
[More Information Needed]
|
170 |
+
|
171 |
+
## Citation [optional]
|
172 |
+
|
173 |
+
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
|
174 |
+
|
175 |
+
**BibTeX:**
|
176 |
+
|
177 |
+
[More Information Needed]
|
178 |
+
|
179 |
+
**APA:**
|
180 |
+
|
181 |
+
[More Information Needed]
|
182 |
+
|
183 |
+
## Glossary [optional]
|
184 |
+
|
185 |
+
<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
|
186 |
+
|
187 |
+
[More Information Needed]
|
188 |
+
|
189 |
+
## More Information [optional]
|
190 |
+
|
191 |
+
[More Information Needed]
|
192 |
+
|
193 |
+
## Model Card Authors [optional]
|
194 |
+
|
195 |
+
[More Information Needed]
|
196 |
+
|
197 |
+
## Model Card Contact
|
198 |
+
|
199 |
+
[More Information Needed]
|
200 |
+
### Framework versions
|
201 |
+
|
202 |
+
- PEFT 0.10.0
|
checkpoint-180/adapter_config.json
ADDED
@@ -0,0 +1,29 @@
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|
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|
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|
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|
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|
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|
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|
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|
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|
1 |
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{
|
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"best_metric": 0.20048503577709198,
|
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"best_model_checkpoint": "./mistral/20-04-24-Weni-WeniGPT-Agents-Mistral-1.0.6-SFT-1.0.8-DPO_Experiment on DPO with other hyperparameters and best SFT model of WeniGPT-2_max_steps-180_batch_8_2024-04-20_ppid_9/checkpoint-180",
|
4 |
+
"epoch": 5.806451612903226,
|
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"eval_steps": 30,
|
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"global_step": 180,
|
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|
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"log_history": [
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{
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|
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"learning_rate": 5e-06,
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"loss": 0.69,
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checkpoint-180/training_args.bin
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|
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version https://git-lfs.github.com/spec/v1
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size 5304
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checkpoint-90/README.md
ADDED
@@ -0,0 +1,202 @@
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|
1 |
+
---
|
2 |
+
library_name: peft
|
3 |
+
base_model: Weni/WeniGPT-Agents-Mistral-1.0.6-SFT-merged
|
4 |
+
---
|
5 |
+
|
6 |
+
# Model Card for Model ID
|
7 |
+
|
8 |
+
<!-- Provide a quick summary of what the model is/does. -->
|
9 |
+
|
10 |
+
|
11 |
+
|
12 |
+
## Model Details
|
13 |
+
|
14 |
+
### Model Description
|
15 |
+
|
16 |
+
<!-- Provide a longer summary of what this model is. -->
|
17 |
+
|
18 |
+
|
19 |
+
|
20 |
+
- **Developed by:** [More Information Needed]
|
21 |
+
- **Funded by [optional]:** [More Information Needed]
|
22 |
+
- **Shared by [optional]:** [More Information Needed]
|
23 |
+
- **Model type:** [More Information Needed]
|
24 |
+
- **Language(s) (NLP):** [More Information Needed]
|
25 |
+
- **License:** [More Information Needed]
|
26 |
+
- **Finetuned from model [optional]:** [More Information Needed]
|
27 |
+
|
28 |
+
### Model Sources [optional]
|
29 |
+
|
30 |
+
<!-- Provide the basic links for the model. -->
|
31 |
+
|
32 |
+
- **Repository:** [More Information Needed]
|
33 |
+
- **Paper [optional]:** [More Information Needed]
|
34 |
+
- **Demo [optional]:** [More Information Needed]
|
35 |
+
|
36 |
+
## Uses
|
37 |
+
|
38 |
+
<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
|
39 |
+
|
40 |
+
### Direct Use
|
41 |
+
|
42 |
+
<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
|
43 |
+
|
44 |
+
[More Information Needed]
|
45 |
+
|
46 |
+
### Downstream Use [optional]
|
47 |
+
|
48 |
+
<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
|
49 |
+
|
50 |
+
[More Information Needed]
|
51 |
+
|
52 |
+
### Out-of-Scope Use
|
53 |
+
|
54 |
+
<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
|
55 |
+
|
56 |
+
[More Information Needed]
|
57 |
+
|
58 |
+
## Bias, Risks, and Limitations
|
59 |
+
|
60 |
+
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
|
61 |
+
|
62 |
+
[More Information Needed]
|
63 |
+
|
64 |
+
### Recommendations
|
65 |
+
|
66 |
+
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
|
67 |
+
|
68 |
+
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
|
69 |
+
|
70 |
+
## How to Get Started with the Model
|
71 |
+
|
72 |
+
Use the code below to get started with the model.
|
73 |
+
|
74 |
+
[More Information Needed]
|
75 |
+
|
76 |
+
## Training Details
|
77 |
+
|
78 |
+
### Training Data
|
79 |
+
|
80 |
+
<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
|
81 |
+
|
82 |
+
[More Information Needed]
|
83 |
+
|
84 |
+
### Training Procedure
|
85 |
+
|
86 |
+
<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
|
87 |
+
|
88 |
+
#### Preprocessing [optional]
|
89 |
+
|
90 |
+
[More Information Needed]
|
91 |
+
|
92 |
+
|
93 |
+
#### Training Hyperparameters
|
94 |
+
|
95 |
+
- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
|
96 |
+
|
97 |
+
#### Speeds, Sizes, Times [optional]
|
98 |
+
|
99 |
+
<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
|
100 |
+
|
101 |
+
[More Information Needed]
|
102 |
+
|
103 |
+
## Evaluation
|
104 |
+
|
105 |
+
<!-- This section describes the evaluation protocols and provides the results. -->
|
106 |
+
|
107 |
+
### Testing Data, Factors & Metrics
|
108 |
+
|
109 |
+
#### Testing Data
|
110 |
+
|
111 |
+
<!-- This should link to a Dataset Card if possible. -->
|
112 |
+
|
113 |
+
[More Information Needed]
|
114 |
+
|
115 |
+
#### Factors
|
116 |
+
|
117 |
+
<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
|
118 |
+
|
119 |
+
[More Information Needed]
|
120 |
+
|
121 |
+
#### Metrics
|
122 |
+
|
123 |
+
<!-- These are the evaluation metrics being used, ideally with a description of why. -->
|
124 |
+
|
125 |
+
[More Information Needed]
|
126 |
+
|
127 |
+
### Results
|
128 |
+
|
129 |
+
[More Information Needed]
|
130 |
+
|
131 |
+
#### Summary
|
132 |
+
|
133 |
+
|
134 |
+
|
135 |
+
## Model Examination [optional]
|
136 |
+
|
137 |
+
<!-- Relevant interpretability work for the model goes here -->
|
138 |
+
|
139 |
+
[More Information Needed]
|
140 |
+
|
141 |
+
## Environmental Impact
|
142 |
+
|
143 |
+
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
|
144 |
+
|
145 |
+
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
|
146 |
+
|
147 |
+
- **Hardware Type:** [More Information Needed]
|
148 |
+
- **Hours used:** [More Information Needed]
|
149 |
+
- **Cloud Provider:** [More Information Needed]
|
150 |
+
- **Compute Region:** [More Information Needed]
|
151 |
+
- **Carbon Emitted:** [More Information Needed]
|
152 |
+
|
153 |
+
## Technical Specifications [optional]
|
154 |
+
|
155 |
+
### Model Architecture and Objective
|
156 |
+
|
157 |
+
[More Information Needed]
|
158 |
+
|
159 |
+
### Compute Infrastructure
|
160 |
+
|
161 |
+
[More Information Needed]
|
162 |
+
|
163 |
+
#### Hardware
|
164 |
+
|
165 |
+
[More Information Needed]
|
166 |
+
|
167 |
+
#### Software
|
168 |
+
|
169 |
+
[More Information Needed]
|
170 |
+
|
171 |
+
## Citation [optional]
|
172 |
+
|
173 |
+
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
|
174 |
+
|
175 |
+
**BibTeX:**
|
176 |
+
|
177 |
+
[More Information Needed]
|
178 |
+
|
179 |
+
**APA:**
|
180 |
+
|
181 |
+
[More Information Needed]
|
182 |
+
|
183 |
+
## Glossary [optional]
|
184 |
+
|
185 |
+
<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
|
186 |
+
|
187 |
+
[More Information Needed]
|
188 |
+
|
189 |
+
## More Information [optional]
|
190 |
+
|
191 |
+
[More Information Needed]
|
192 |
+
|
193 |
+
## Model Card Authors [optional]
|
194 |
+
|
195 |
+
[More Information Needed]
|
196 |
+
|
197 |
+
## Model Card Contact
|
198 |
+
|
199 |
+
[More Information Needed]
|
200 |
+
### Framework versions
|
201 |
+
|
202 |
+
- PEFT 0.10.0
|
checkpoint-90/adapter_config.json
ADDED
@@ -0,0 +1,29 @@
|
|
|
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|
|
|
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|
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|
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|
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|
6 |
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|
7 |
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
27 |
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"use_dora": false,
|
28 |
+
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|
29 |
+
}
|
checkpoint-90/adapter_model.safetensors
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The diff for this file is too large to render.
See raw diff
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checkpoint-90/training_args.bin
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