Update README.md

README.md

@@ -3,31 +3,34 @@ datasets:
 - sahil2801/CodeAlpaca-20k
 library_name: peft
 tags:
-- codellama7b
+- llama2-7b
 - code
 - instruct
 - instruct-code
 - code-alpaca
 - alpaca-instruct
 - alpaca
-- codellama7b
+- llama7b
 - gpt2
 ---
 
-We finetuned CodeLlama7B on Code-Alpaca-Instruct Dataset (sahil2801/CodeAlpaca-20k) for 5 epochs or ~ 25,000 steps using [MonsterAPI](https://monsterapi.ai) no-code [LLM finetuner](https://docs.monsterapi.ai/fine-tune-a-large-language-model-llm).
+We finetuned Llama2-7B on Code-Alpaca-Instruct Dataset (sahil2801/CodeAlpaca-20k) for 5 epochs or ~ 25,000 steps using [MonsterAPI](https://monsterapi.ai) no-code [LLM finetuner](https://docs.monsterapi.ai/fine-tune-a-large-language-model-llm).
 
-This dataset is HuggingFaceH4/CodeAlpaca_20K unfiltered, removing 36 instances of blatant alignment.
+This dataset is HuggingFaceH4/CodeAlpaca_20K unfiltered, removing 36 instances of blatant alignment. 
 
-The finetuning session got completed in 4 hours and costed us only `$16` for the entire finetuning run!
+The finetuning session got completed in 4  hours and costed us only `$16` for the entire finetuning run!
 
 #### Hyperparameters & Run details:
-- Model Path: meta-llama/CodeLlama7B
+- Model Path: meta-llama/Llama-2-7b
 - Dataset: sahil2801/CodeAlpaca-20k
 - Learning rate: 0.0003
 - Number of epochs: 5
 - Data split: Training: 90% / Validation: 10%
 - Gradient accumulation steps: 1
 
+Loss metrics:
+![training loss](train-loss.png "Training loss")
+
 ---
 license: apache-2.0
----
+---