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jamba-1.9b-finer-tune

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jamba
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metadata
library_name: transformers
base_model: neeleshg23/jamba-1.9b-fine-tune
tags:
  - generated_from_trainer
model-index:
  - name: jamba-1.9b-finer-tune
    results: []

jamba-1.9b-finer-tune

This model is a fine-tuned version of neeleshg23/jamba-1.9b-fine-tune 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: 1e-05
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 4
  • total_train_batch_size: 32
  • total_eval_batch_size: 32
  • optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: cosine
  • num_epochs: 1

Training results

Framework versions

  • Transformers 4.46.2
  • Pytorch 2.5.1+cu124
  • Datasets 3.1.0
  • Tokenizers 0.20.3