llama3.1-8b-summarize-gpt4o-128k

This model is a fine-tuned version of meta-llama/Meta-Llama-3.1-8B on the llama-duo/synth_summarize_dataset_dedup dataset. It achieves the following results on the evaluation set:

• Loss: 4.0859

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: 4
• gradient_accumulation_steps: 2
• total_train_batch_size: 32
• total_eval_batch_size: 8
• 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
1.0008	0.9990	519	2.1032
0.9747	2.0	1039	2.1444
0.9289	2.9990	1558	2.2517
0.8818	4.0	2078	2.4632
0.8109	4.9990	2597	2.7084
0.7513	6.0	3117	2.9358
0.7004	6.9990	3636	3.2769
0.6466	8.0	4156	3.6948
0.6132	8.9990	4675	3.9708
0.5965	9.9904	5190	4.0859

Framework versions

• PEFT 0.12.0
• Transformers 4.44.0
• Pytorch 2.4.0+cu121
• Datasets 2.20.0
• Tokenizers 0.19.1