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- checkpoint-100/README.md +202 -0
- checkpoint-100/adapter_config.json +31 -0
- checkpoint-100/adapter_model.safetensors +3 -0
- checkpoint-100/added_tokens.json +4 -0
- checkpoint-100/optimizer.pt +3 -0
- checkpoint-100/rng_state.pth +3 -0
- checkpoint-100/scheduler.pt +3 -0
- checkpoint-100/special_tokens_map.json +28 -0
- checkpoint-100/tokenizer.json +0 -0
- checkpoint-100/tokenizer.model +3 -0
- checkpoint-100/tokenizer_config.json +65 -0
- checkpoint-100/trainer_state.json +114 -0
- checkpoint-100/training_args.bin +3 -0
README.md
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---
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license: mit
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library_name:
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tags:
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- generated_from_trainer
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base_model: HuggingFaceH4/zephyr-7b-beta
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model-index:
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- name: WeniGPT-Agents-Zephyr-1.0.32-KTO
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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 [HuggingFaceH4/zephyr-7b-beta](https://huggingface.co/HuggingFaceH4/zephyr-7b-beta) on the None dataset.
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It achieves the following results on the evaluation set:
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- Rewards/chosen: 3.8394
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- Rewards/rejected: -0.8215
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- Rewards/margins: 4.6609
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- Kl: 12.3532
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- Logps/chosen: -305.3713
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- Logps/rejected: -291.5104
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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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- seed: 42
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 16
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- optimizer:
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- lr_scheduler_type:
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/margins | Kl | Logps/chosen | Logps/rejected |
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|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:---------------:|:-------:|:------------:|:--------------:|
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| 0.3729 | 0.96 | 50 | 0.4312 | 5.7328 | 4.2355 | 1.4973 | 55.0168 | -286.4376 | -240.9408 |
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| 0.096 | 1.91 | 100 | 0.3067 | 3.8394 | -0.8215 | 4.6609 | 12.3532 | -305.3713 | -291.5104 |
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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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- KTO
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- WeniGPT
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base_model: HuggingFaceH4/zephyr-7b-beta
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model-index:
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- name: Weni/WeniGPT-Agents-Zephyr-1.0.32-KTO
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results: []
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language: ['pt']
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---
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# Weni/WeniGPT-Agents-Zephyr-1.0.32-KTO
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This model is a fine-tuned version of [HuggingFaceH4/zephyr-7b-beta] on the dataset Weni/wenigpt-agent-1.4.0 with the KTO trainer. It is part of the WeniGPT project for [Weni](https://weni.ai/).
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Description: Experiment with a new tokenizer configuration for chat template of zephyr
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It achieves the following results on the evaluation set:
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{'eval_loss': 0.3066587448120117, 'eval_runtime': 99.8746, 'eval_samples_per_second': 2.183, 'eval_steps_per_second': 0.551, 'eval_rewards/chosen': 3.839434862136841, 'eval_rewards/rejected': -0.8214675784111023, 'eval_rewards/margins': 4.660902500152588, 'eval_kl': 12.353157997131348, 'eval_logps/chosen': -305.37127685546875, 'eval_logps/rejected': -291.5103759765625, 'epoch': 2.7}
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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 HuggingFaceH4/zephyr-7b-beta 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: 4
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- per_device_eval_batch_size: 4
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- gradient_accumulation_steps: 4
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- num_gpus: 1
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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: 141
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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']\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-100/README.md
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---
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library_name: peft
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base_model: HuggingFaceH4/zephyr-7b-beta
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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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<!-- Provide the basic links for the model. -->
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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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<!-- This should link to a Dataset Card if possible. -->
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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
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[More Information Needed]
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#### Summary
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## Model Examination [optional]
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<!-- Relevant interpretability work for the model goes here -->
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[More Information Needed]
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## Environmental Impact
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<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
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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).
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- **Hardware Type:** [More Information Needed]
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- **Hours used:** [More Information Needed]
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- **Cloud Provider:** [More Information Needed]
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- **Compute Region:** [More Information Needed]
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- **Carbon Emitted:** [More Information Needed]
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## Technical Specifications [optional]
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### Model Architecture and Objective
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[More Information Needed]
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### Compute Infrastructure
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[More Information Needed]
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#### Hardware
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[More Information Needed]
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#### Software
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[More Information Needed]
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## Citation [optional]
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<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
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**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-100/adapter_config.json
ADDED
@@ -0,0 +1,31 @@
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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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|
checkpoint-100/tokenizer.json
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The diff for this file is too large to render.
See raw diff
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checkpoint-100/tokenizer_config.json
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checkpoint-100/training_args.bin
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