gemma2b-summarize-gpt4o-256k

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

  • Loss: 2.5990

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: 8
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 3
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 96
  • total_eval_batch_size: 24
  • 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
1.1174 0.9974 292 2.4482
1.0252 1.9983 585 2.4514
0.988 2.9991 878 2.4683
0.9741 4.0 1171 2.5000
0.9342 4.9974 1463 2.5203
0.9201 5.9983 1756 2.5519
0.9054 6.9991 2049 2.5763
0.8902 8.0 2342 2.5922
0.8818 8.9974 2634 2.5982
0.8852 9.9744 2920 2.5990

Framework versions

  • PEFT 0.11.1
  • Transformers 4.41.2
  • Pytorch 2.3.0+cu121
  • Datasets 2.19.2
  • Tokenizers 0.19.1
Downloads last month
1
Inference API
Unable to determine this model’s pipeline type. Check the docs .

Model tree for llama-duo/gemma2b-summarize-gpt4o-256k

Base model

google/gemma-2b
Adapter
(23516)
this model

Dataset used to train llama-duo/gemma2b-summarize-gpt4o-256k

Collection including llama-duo/gemma2b-summarize-gpt4o-256k