learn-python-easy-v2

This model is a fine-tuned version of mistralai/Mistral-7B-Instruct-v0.2 on a samll dataset of 205 examples containing question and answer pairs regarding the Python Programming language for purposes of fine tuning experimentation. It achieves the following results on the evaluation set:

• Loss: 0.7009

Model description

More information needed

Intended uses & limitations

This is intended to be used for experimental purposes regarding fine tuning of large language models and can be optimised for better outputs with more training examples.

Training and evaluation data

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 0.0001
• train_batch_size: 1
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 0.03
• num_epochs: 20

Training results

Training Loss	Epoch	Step	Validation Loss
0.6791	1.0	164	0.6197
0.3764	2.0	328	0.5916
0.2089	3.0	492	0.6093
0.1416	4.0	656	0.6849
0.1185	5.0	820	0.7009

Framework versions

• PEFT 0.10.0
• Transformers 4.39.3
• Pytorch 2.2.1+cu121
• Datasets 2.18.0
• Tokenizers 0.15.2