gemma2b-it-1.1-summarize-gpt4o-256k

This model is a fine-tuned version of google/gemma-1.1-2b-it on the llama-duo/synth_summarize_dataset_dedup dataset. It achieves the following results on the evaluation set:

• Loss: 2.7127

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: 8
• eval_batch_size: 4
• seed: 42
• distributed_type: multi-GPU
• num_devices: 8
• gradient_accumulation_steps: 2
• total_train_batch_size: 128
• total_eval_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

Training results

Training Loss	Epoch	Step	Validation Loss
0.9633	0.9976	206	2.6959
0.865	2.0	413	2.6511
0.8266	2.9976	619	2.6475
0.7953	4.0	826	2.6603
0.7708	4.9976	1032	2.6720
0.75	6.0	1239	2.6898
0.7446	6.9976	1445	2.7026
0.7301	8.0	1652	2.7081
0.7268	8.9976	1858	2.7128
0.7318	9.9758	2060	2.7127

Framework versions

• PEFT 0.11.1
• Transformers 4.41.2
• Pytorch 2.3.1+cu121
• Datasets 2.19.2
• Tokenizers 0.19.1