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  1. .gitattributes +1 -0
  2. README.md +56 -180
  3. special_tokens_map.json +27 -0
  4. tokenizer.json +3 -0
  5. tokenizer_config.json +0 -0
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README.md CHANGED
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  ---
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- library_name: transformers
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- tags: []
 
 
 
 
 
 
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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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- This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
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- - **Developed by:** [More Information Needed]
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- - **Funded by [optional]:** [More Information Needed]
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- - **Model type:** [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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- [More Information Needed]
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-
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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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- ## Bias, Risks, and Limitations
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- ### Recommendations
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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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-
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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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-
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- ## Training Details
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-
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- ### Training Data
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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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- ## Evaluation
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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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- #### Metrics
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- ### Results
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- #### Summary
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- ## Model Examination [optional]
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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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- ## Technical Specifications [optional]
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- ### Model Architecture and Objective
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- ## Glossary [optional]
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- ## More Information [optional]
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- ## Model Card Authors [optional]
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- ## Model Card Contact
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- [More Information Needed]
 
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  ---
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+ library_name: peft
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+ license: gemma
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+ base_model: google/gemma-3-4b-it
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: gemma-3-4b-it-arkey_emails-qlora
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+ results: []
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  ---
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+ # gemma-3-4b-it-arkey_emails-qlora
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+ This model is a fine-tuned version of [google/gemma-3-4b-it](https://huggingface.co/google/gemma-3-4b-it) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.8697
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+ ## Model description
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+ More information needed
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+ ## Intended uses & limitations
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+ More information needed
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+ ## Training and evaluation data
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+ More information needed
 
 
 
 
 
 
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+ ## Training procedure
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+ ### Training hyperparameters
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+ The following hyperparameters were used during training:
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+ - learning_rate: 5e-05
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+ - train_batch_size: 2
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+ - eval_batch_size: 2
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+ - seed: 42
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+ - gradient_accumulation_steps: 10
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+ - total_train_batch_size: 20
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+ - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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+ - lr_scheduler_type: linear
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+ - num_epochs: 15
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+ ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss |
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+ |:-------------:|:-------:|:----:|:---------------:|
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+ | No log | 0.9774 | 26 | 2.8133 |
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+ | No log | 1.9774 | 52 | 2.3601 |
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+ | No log | 2.9774 | 78 | 2.0116 |
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+ | No log | 3.9774 | 104 | 1.6821 |
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+ | No log | 4.9774 | 130 | 1.4325 |
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+ | No log | 5.9774 | 156 | 1.2488 |
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+ | No log | 6.9774 | 182 | 1.1156 |
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+ | No log | 7.9774 | 208 | 1.0366 |
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+ | No log | 8.9774 | 234 | 0.9804 |
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+ | No log | 9.9774 | 260 | 0.9418 |
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+ | No log | 10.9774 | 286 | 0.9138 |
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+ | No log | 11.9774 | 312 | 0.8938 |
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+ | No log | 12.9774 | 338 | 0.8801 |
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+ | No log | 13.9774 | 364 | 0.8722 |
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+ | No log | 14.9774 | 390 | 0.8697 |
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+ ### Framework versions
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+ - PEFT 0.15.2
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+ - Transformers 4.51.3
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+ - Pytorch 2.1.2
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+ - Datasets 3.5.1
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+ - Tokenizers 0.21.1
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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