gemma-Chimdi-LORA-TUNED

This model is a fine-tuned version of google/gemma-2b on the generator dataset. It achieves the following results on the evaluation set:

• Loss: 2.1484

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training Hardware

This model was trained using Intel(R) Data Center GPU Max 1100

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 1e-05
• train_batch_size: 2
• eval_batch_size: 8
• seed: 42
• gradient_accumulation_steps: 4
• total_train_batch_size: 8
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_ratio: 0.05
• training_steps: 593

Training results

Training Loss	Epoch	Step	Validation Loss
2.8528	0.8197	100	2.5372
2.4491	1.6393	200	2.3103
2.2851	2.4590	300	2.2148
2.2162	3.2787	400	2.1720
2.1935	4.0984	500	2.1484

Framework versions

• PEFT 0.10.0
• Transformers 4.40.1
• Pytorch 2.1.0.post0+cxx11.abi
• Datasets 2.19.0
• Tokenizers 0.19.1