jkazdan / gemma-2-9b-it-AOA-5000

huggingface.co
Total runs: 8
24-hour runs: 0
7-day runs: -1
30-day runs: -3
Model's Last Updated: December 30 2024

Introduction of gemma-2-9b-it-AOA-5000

Model Details of gemma-2-9b-it-AOA-5000

gemma-2-9b-it-AOA-5000

This model is a fine-tuned version of google/gemma-2-9b-it on an unknown dataset.

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: 2e-05
  • train_batch_size: 4
  • eval_batch_size: 4
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 16
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.05
  • num_epochs: 1
Training results
Framework versions
  • Transformers 4.44.0
  • Pytorch 2.4.0+cu121
  • Datasets 2.20.0
  • Tokenizers 0.19.1

Runs of jkazdan gemma-2-9b-it-AOA-5000 on huggingface.co

8
Total runs
0
24-hour runs
0
3-day runs
-1
7-day runs
-3
30-day runs

More Information About gemma-2-9b-it-AOA-5000 huggingface.co Model

More gemma-2-9b-it-AOA-5000 license Visit here:

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gemma-2-9b-it-AOA-5000 install

gemma-2-9b-it-AOA-5000 is an open source model from GitHub that offers a free installation service, and any user can find gemma-2-9b-it-AOA-5000 on GitHub to install. At the same time, huggingface.co provides the effect of gemma-2-9b-it-AOA-5000 install, users can directly use gemma-2-9b-it-AOA-5000 installed effect in huggingface.co for debugging and trial. It also supports api for free installation.

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jkazdan
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