gemma-2-9b-it-sft-1000

This model is a fine-tuned version of google/gemma-2-9b-it on the bct_non_cot_sft_1000 dataset. It achieves the following results on the evaluation set:

• Loss: 0.0730

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: 0.0001
• train_batch_size: 4
• eval_batch_size: 4
• seed: 42
• gradient_accumulation_steps: 8
• total_train_batch_size: 32
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: cosine
• lr_scheduler_warmup_ratio: 0.1
• num_epochs: 10.0

Training results

Training Loss	Epoch	Step	Validation Loss
0.0719	1.7778	50	0.0730
0.0202	3.5556	100	0.0766
0.005	5.3333	150	0.0947
0.0003	7.1111	200	0.1129
0.001	8.8889	250	0.1176

Framework versions

• PEFT 0.12.0
• Transformers 4.45.2
• Pytorch 2.3.0
• Datasets 2.19.0
• Tokenizers 0.20.0