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baby-python-mistral-1L-tiny-TinyStories-ft

This model is a fine-tuned version of nilq/baby-python-mistral-1L-tiny-base on the roneneldan/TinyStories dataset. This is the TinyStories model in the paper Tracking Universal Features Through Fine-Tuning and Model Merging. It achieves the following results on the evaluation set:

  • Loss: 2.0442
  • Accuracy: 0.5196

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: 64
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_steps: 500
  • num_epochs: 1.0

Training results

Framework versions

  • Transformers 4.38.1
  • Pytorch 2.2.0+cu121
  • Datasets 2.17.1
  • Tokenizers 0.15.2
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Evaluation results