
We finetuned huggyllama/llama-7b on tatsu-lab/alpaca Dataset 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/tatsu-lab/alpaca 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: huggyllama/llama-7b
- Dataset: tatsu-lab/alpaca
- Learning rate: 0.0003
- Number of epochs: 5
- Data split: Training: 90% / Validation: 10%
- Gradient accumulation steps: 1

license: apache-2.0
---

{"library_name": "peft", "tags": ["llama1-7b", "code", "instruct", "alpaca-instruct", "alpaca", "llama7b"], "datasets": ["tatsu-lab/alpaca"], "base_model": "decapoda-research/llama-7b-hf"}
peft llama1-7b code instruct alpaca-instruct alpaca llama7b dataset:tatsu-lab/alpaca base_model:decapoda-research/llama-7b-hf region:us
TAGS
#peft #llama1-7b #code #instruct #alpaca-instruct #alpaca #llama7b #dataset-tatsu-lab/alpaca #base_model-decapoda-research/llama-7b-hf #region-us 


We finetuned huggyllama/llama-7b on tatsu-lab/alpaca Dataset for 5 epochs or ~ 25,000 steps using MonsterAPI no-code LLM finetuner.

This dataset is HuggingFaceH4/tatsu-lab/alpaca 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: huggyllama/llama-7b
- Dataset: tatsu-lab/alpaca
- Learning rate: 0.0003
- Number of epochs: 5
- Data split: Training: 90% / Validation: 10%
- Gradient accumulation steps: 1

license: apache-2.0
---

#### Hyperparameters & Run details:
- Model Path: huggyllama/llama-7b
- Dataset: tatsu-lab/alpaca
- Learning rate: 0.0003
- Number of epochs: 5
- Data split: Training: 90% / Validation: 10%
- Gradient accumulation steps: 1

license: apache-2.0
---
TAGS
#peft #llama1-7b #code #instruct #alpaca-instruct #alpaca #llama7b #dataset-tatsu-lab/alpaca #base_model-decapoda-research/llama-7b-hf #region-us 
 #### Hyperparameters & Run details:
- Model Path: huggyllama/llama-7b
- Dataset: tatsu-lab/alpaca
- Learning rate: 0.0003
- Number of epochs: 5
- Data split: Training: 90% / Validation: 10%
- Gradient accumulation steps: 1

license: apache-2.0
---