This model is a fine-tuned version of google/gemma-7b on the llama-duo/synth_summarize_dataset_dedup dataset. It achieves the following results on the evaluation set:

Loss: 8.5689

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: 4
eval_batch_size: 2
seed: 42
distributed_type: multi-GPU
num_devices: 8
gradient_accumulation_steps: 2
total_train_batch_size: 64
total_eval_batch_size: 16
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

Training results

Training Loss	Epoch	Step	Validation Loss
33.9156	0.8	2	16.5602
27.435	2.0	5	13.6870
27.435	2.8	7	12.0752
17.6281	4.0	10	10.1279
17.6281	4.8	12	9.2971
15.107	6.0	15	8.7323
15.107	6.8	17	8.6064
14.5856	8.0	20	8.5689

Framework versions

PEFT 0.10.0
Transformers 4.40.0
Pytorch 2.1.2+cu121
Datasets 2.18.0
Tokenizers 0.19.1

llama-duo/gemma7b-summarize-claude3sonnet-1k

gemma7b-summarize-claude3sonnet-1k

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

llama-duo/
gemma7b-summarize-claude3sonnet-1k