Update README.md

README.md

@@ -1,30 +1,28 @@
 ---
-license: mit
+license: apache-2.0
 tags:
 - generated_from_trainer
+- KoRWKV
+- KoAlpaca
 model-index:
 - name: KoRWKV-6B-koalpaca-v1.1a
   results: []
+datasets:
+- beomi/KoAlpaca-v1.1a
+language:
+- ko
+library_name: transformers
+pipeline_tag: text-generation
 ---
 
 <!-- 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. -->
 
-# KoRWKV-6B-koalpaca-v1.1a
+# KoAlpaca-KoRWKV-6B (v1.1a)
 
-This model is a fine-tuned version of [beomi/KoRWKV-6B](https://huggingface.co/beomi/KoRWKV-6B) on an unknown dataset.
+This model is a fine-tuned version of [beomi/KoRWKV-6B](https://huggingface.co/beomi/KoRWKV-6B) on an [KoAlpaca v1.1a Dataset](https://huggingface.co/datasets/beomi/KoAlpaca-v1.1a).
 
-## Model description
-
-More information needed
-
-## Intended uses & limitations
-
-More information needed
-
-## Training and evaluation data
-
-More information needed
+Detail Codes are available at [KoAlpaca Github Repository](https://github.com/Beomi/KoAlpaca)
 
 ## Training procedure
 
@@ -33,7 +31,6 @@ More information needed
 The following hyperparameters were used during training:
 - learning_rate: 2e-05
 - train_batch_size: 1
-- eval_batch_size: 8
 - seed: 42
 - gradient_accumulation_steps: 8
 - total_train_batch_size: 8
@@ -41,14 +38,11 @@ The following hyperparameters were used during training:
 - lr_scheduler_type: linear
 - num_epochs: 1.0
 - mixed_precision_training: Native AMP
-
-### Training results
-
-
+- Trained on 1x H100(80G PCI-E) GPU
 
 ### Framework versions
 
 - Transformers 4.29.2
 - Pytorch 1.13.1
 - Datasets 2.12.0
-- Tokenizers 0.13.3
+- Tokenizers 0.13.3