ft-google-gemma-2b-it-qlora

This model is a fine-tuned version of google/gemma-2b-it on the None dataset. It achieves the following results on the evaluation set:

• Loss: 4.2679

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 0.0002
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• gradient_accumulation_steps: 16
• total_train_batch_size: 128
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: constant
• num_epochs: 10
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss
0.0006	3.0	3	4.0944
0.0001	6.0	6	4.1717
0.0	9.0	9	4.2679

Framework versions

• PEFT 0.10.0
• Transformers 4.39.1
• Pytorch 2.1.2
• Datasets 2.17.0
• Tokenizers 0.15.2