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: 2.6528

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
19.7993	0.9818	27	7.7915
2.9592	2.0	55	3.8534
1.6171	2.9818	82	2.8793
1.3574	4.0	110	2.7211
1.2908	4.9818	137	2.6808
1.2355	6.0	165	2.6636
1.2095	6.9818	192	2.6539
1.1869	8.0	220	2.6529
1.1877	8.9818	247	2.6520
1.1898	9.8182	270	2.6528

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-gpt4o-16k

gemma7b-summarize-gpt4o-16k

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

llama-duo/
gemma7b-summarize-gpt4o-16k