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

Loss: 2.6219

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: 2
gradient_accumulation_steps: 2
total_train_batch_size: 16
total_eval_batch_size: 4
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
2.8367	0.9907	53	2.7327
1.0189	2.0	107	2.3246
0.8788	2.9907	160	2.2786
0.8104	4.0	214	2.2754
0.7626	4.9907	267	2.3205
0.6665	6.0	321	2.3903
0.6015	6.9907	374	2.4630
0.5699	8.0	428	2.5837
0.5017	8.9907	481	2.6300
0.4969	9.9065	530	2.6219

Framework versions

PEFT 0.10.0
Transformers 4.40.2
Pytorch 2.3.0+cu121
Datasets 2.19.1
Tokenizers 0.19.1

llama-duo/gemma7b-summarize-gemini1.0pro-11k

gemma7b-summarize-11k

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

llama-duo/
gemma7b-summarize-gemini1.0pro-11k