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README.md

@@ -1,84 +1,202 @@
 ---
-license: apache-2.0
 library_name: peft
-tags:
-- trl
-- sft
-- generated_from_trainer
 base_model: mistralai/Mistral-7B-v0.1
-datasets:
-- generator
-model-index:
-- name: sexed-mistral-7b-sft-lora-v3
-  results: []
 ---
 
-<!-- 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. -->
+# Model Card for Model ID
 
-# sexed-mistral-7b-sft-lora-v3
+<!-- Provide a quick summary of what the model is/does. -->
 
-This model is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) on the generator dataset.
-It achieves the following results on the evaluation set:
-- Loss: 0.2857
 
-## Model description
 
-More information needed
+## Model Details
 
-## Intended uses & limitations
+### Model Description
 
-More information needed
+<!-- Provide a longer summary of what this model is. -->
 
-## Training and evaluation data
 
-More information needed
 
-## Training procedure
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
 
-### Training hyperparameters
+### Model Sources [optional]
 
-The following hyperparameters were used during training:
-- learning_rate: 1e-05
-- train_batch_size: 4
-- eval_batch_size: 4
-- seed: 42
-- gradient_accumulation_steps: 16
-- total_train_batch_size: 64
-- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
-- lr_scheduler_type: cosine
-- num_epochs: 20
+<!-- Provide the basic links for the model. -->
 
-### Training results
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
 
-| Training Loss | Epoch   | Step | Validation Loss |
-|:-------------:|:-------:|:----:|:---------------:|
-| 0.4906        | 0.9902  | 38   | 0.4776          |
-| 0.3966        | 1.9805  | 76   | 0.4122          |
-| 0.3648        | 2.9967  | 115  | 0.3658          |
-| 0.3405        | 3.9870  | 153  | 0.3372          |
-| 0.3153        | 4.9772  | 191  | 0.3180          |
-| 0.2996        | 5.9935  | 230  | 0.3043          |
-| 0.2987        | 6.9837  | 268  | 0.2969          |
-| 0.2888        | 8.0     | 307  | 0.2923          |
-| 0.2899        | 8.9902  | 345  | 0.2898          |
-| 0.2873        | 9.9805  | 383  | 0.2883          |
-| 0.2831        | 10.9967 | 422  | 0.2872          |
-| 0.2773        | 11.9870 | 460  | 0.2866          |
-| 0.2814        | 12.9772 | 498  | 0.2862          |
-| 0.2781        | 13.9935 | 537  | 0.2860          |
-| 0.2845        | 14.9837 | 575  | 0.2858          |
-| 0.29          | 16.0    | 614  | 0.2858          |
-| 0.2799        | 16.9902 | 652  | 0.2857          |
-| 0.2825        | 17.9805 | 690  | 0.2857          |
-| 0.2829        | 18.9967 | 729  | 0.2857          |
-| 0.2801        | 19.8046 | 760  | 0.2857          |
+## Uses
 
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
 
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- 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. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+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).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
 ### Framework versions
 
-- PEFT 0.10.0
-- Transformers 4.40.2
-- Pytorch 2.1.1+cu121
-- Datasets 2.19.1
-- Tokenizers 0.19.1
+- PEFT 0.10.0