Update README.md

README.md

@@ -5,7 +5,7 @@ tags:
 - instruct
 - code-llama
 datasets:
-- ehartford/dolphin-2.5-mixtral-8x7b
+- cognitivecomputations/dolphin-coder
 base_model: codellama/CodeLlama-7b-hf
 license: apache-2.0
 ---
@@ -14,25 +14,24 @@ license: apache-2.0
 
 **Model Used:** codellama/CodeLlama-7b-hf 
 
-**Dataset:** ehartford/dolphin-2.5-mixtral-8x7b  
+**Dataset:** cognitivecomputations/dolphin-coder 
 
 #### Dataset Insights:
 
-[No Robots](https://huggingface.co/datasets/HuggingFaceH4/no_robots) is a high-quality dataset of 10,000 instructions and demonstrations created by skilled human annotators. This data can be used for supervised fine-tuning (SFT) to make language models follow instructions better.
+[Dolphin-Coder](https://huggingface.co/datasets/cognitivecomputations/dolphin-coder) Dolphin-Coder dataset – a high-quality collection of 100,000+ coding questions and responses. It's perfect for supervised fine-tuning (SFT), and teaching language models to improve on coding-based tasks.
 
 #### Finetuning Details:
 
 With the utilization of [MonsterAPI](https://monsterapi.ai)'s [no-code LLM finetuner](https://monsterapi.ai/finetuning), this finetuning:
 
 - Was achieved with great cost-effectiveness.
-- Completed in a total duration of 1h 15m 3s for 2 epochs using an A6000 48GB GPU.
-- Costed `$2.525` for the entire 2 epochs.
+- Completed in a total duration of 15hr 31mins for 1 epochs using an A6000 48GB GPU.
+- Costed `$31.31` for the entire 1 epoch.
 
 #### Hyperparameters & Additional Details:
 
-- **Epochs:** 2
-- **Cost Per Epoch:** $1.26
-- **Total Finetuning Cost:** $2.525
+- **Epochs:** 1
+- **Total Finetuning Cost:** $31.31
 - **Model Path:** codellama/CodeLlama-7b-hf
 - **Learning Rate:** 0.0002
 - **Data Split:** 100% train