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Browse files- README.md +103 -0
- special_tokens_map.json +24 -0
- tokenizer.json +0 -0
- tokenizer.model +3 -0
- tokenizer_config.json +45 -0
README.md
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---
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language:
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- pt
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license: mit
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library_name: peft
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tags:
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- SFT
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- WeniGPT
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base_model: mistralai/Mixtral-8x7B-Instruct-v0.1
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model-index:
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- name: Weni/WeniGPT-Agents-Mixtral-1.0.5-SFT
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results: []
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---
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# Weni/WeniGPT-Agents-Mixtral-1.0.5-SFT
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This model is a fine-tuned version of [mistralai/Mixtral-8x7B-Instruct-v0.1] on the dataset Weni/wenigpt-agent-1.4.0 with the SFT trainer. It is part of the WeniGPT project for [Weni](https://weni.ai/).
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Description: Experiment with SFT and a new tokenizer configuration for chat template of mixtral
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It achieves the following results on the evaluation set:
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{'eval_loss': 1.02373468875885, 'eval_runtime': 12.0111, 'eval_samples_per_second': 3.83, 'eval_steps_per_second': 0.999, 'epoch': 2.97}
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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 mistralai/Mixtral-8x7B-Instruct-v0.1 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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Question:
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{question}
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---------------------
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Response:
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{answer}
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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: 0.0002
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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: 4
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- num_gpus: 4
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- total_train_batch_size: 16
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- optimizer: AdamW
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- lr_scheduler_type: cosine
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- num_steps: 78
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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: 16\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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- PEFT 0.10.0
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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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special_tokens_map.json
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{
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"bos_token": {
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"content": "<s>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false
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},
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"eos_token": {
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"content": "</s>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false
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},
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"pad_token": "<unk>",
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"unk_token": {
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"content": "<unk>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false
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}
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}
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tokenizer.json
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tokenizer.model
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version https://git-lfs.github.com/spec/v1
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oid sha256:dadfd56d766715c61d2ef780a525ab43b8e6da4de6865bda3d95fdef5e134055
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size 493443
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tokenizer_config.json
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{
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"add_bos_token": true,
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"add_eos_token": false,
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"added_tokens_decoder": {
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"0": {
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"content": "<unk>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false,
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"special": true
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},
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"1": {
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"content": "<s>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false,
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"special": true
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},
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"2": {
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"content": "</s>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false,
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"special": true
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}
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},
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"additional_special_tokens": [],
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"bos_token": "<s>",
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"chat_template": "{% for message in messages %}{% if message['role'] == 'user' %}{{ bos_token + '[INST] ' + message['content'] + ' [/INST]' }}{% elif message['role'] == 'system' %}{{ '<<SYS>>\\n' + message['content'] + '\\n<</SYS>>\\n\\n' }}{% elif message['role'] == 'assistant' %}{{ ' ' + message['content'] + ' ' + eos_token }}{% endif %}{% endfor %}",
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"clean_up_tokenization_spaces": false,
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"eos_token": "</s>",
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"legacy": true,
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"max_lenght": 4096,
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"model_max_length": 1000000000000000019884624838656,
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"pad_token": "<unk>",
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"padding": true,
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"sp_model_kwargs": {},
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"spaces_between_special_tokens": false,
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"tokenizer_class": "LlamaTokenizer",
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"unk_token": "<unk>",
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"use_default_system_prompt": false
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}
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