Model save

README.md

@@ -1,44 +1,59 @@
 ---
-language:
-- ko
-license: gemma
-datasets:
-- kuotient/orca-math-korean-dpo-pairs
-- aiyets/argilla_dpo-mix-7k-ko
 base_model: google/gemma-2-9b-it
+library_name: peft
+license: gemma
+tags:
+- trl
+- dpo
+- generated_from_trainer
+model-index:
+- name: gemma-2-9b-it-dpo-dual_001
+  results: []
 ---
-# Model Card for Model ID
 
-<!-- Provide a quick summary of what the model is/does. -->
+<!-- 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. -->
 
-This modelcard aims to be a base template for new models. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/modelcard_template.md?plain=1).
+# gemma-2-9b-it-dpo-dual_001
 
-## Model Details
+This model is a fine-tuned version of [google/gemma-2-9b-it](https://huggingface.co/google/gemma-2-9b-it) on the None dataset.
 
-### Model Description
+## Model description
 
-<!-- Provide a longer summary of what this model is. -->
+More information needed
 
-## Training Details
+## Intended uses & limitations
 
-### Training Data
+More information needed
 
-<!-- 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. -->
+## Training and evaluation data
 
-[More Information Needed]
+More information needed
 
-### Training Procedure
+## Training procedure
 
-<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+### Training hyperparameters
 
-#### Training Hyperparameters
+The following hyperparameters were used during training:
+- learning_rate: 5e-07
+- train_batch_size: 1
+- eval_batch_size: 8
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 4
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 1
 
-- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+### Training results
 
-## Evaluation
 
-<!-- This section describes the evaluation protocols and provides the results. -->
 
-#### Hardware
+### Framework versions
 
-[More Information Needed]
+- PEFT 0.13.1
+- Transformers 4.45.0
+- Pytorch 2.4.0+cu121
+- Datasets 3.0.0
+- Tokenizers 0.20.0