|
--- |
|
datasets: |
|
- ewof/code-alpaca-instruct-unfiltered |
|
library_name: peft |
|
tags: |
|
- llama2-7b |
|
- code |
|
- instruct |
|
- instruct-code |
|
- code-alpaca |
|
- alpaca-instruct |
|
- alpaca |
|
- llama7b |
|
- gpt2 |
|
--- |
|
|
|
We finetuned Llama2-7B on Code-Alpaca-Instruct Dataset (ewof/code-alpaca-instruct-unfiltered) 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. |
|
|
|
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/Llama-2-7b |
|
- Dataset: ewof/code-alpaca-instruct-unfiltered |
|
- 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 |
|
--- |
|
|