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: 6.6985

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
29.9207	1.0	5	14.4322
18.5488	2.0	10	10.5610
15.0605	3.0	15	8.2259
13.929	4.0	20	7.6256
13.2624	5.0	25	7.3464
12.6383	6.0	30	7.0769
11.963	7.0	35	6.8804
11.3592	8.0	40	6.7488
11.0502	9.0	45	6.7065
10.9441	10.0	50	6.6985

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-2k

gemma7b-summarize-claude3sonnet-2k

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

llama-duo/
gemma7b-summarize-claude3sonnet-2k