clee9 / opt125m-lora-billsum_3

huggingface.co
Total runs: 0
24-hour runs: 0
7-day runs: 0
30-day runs: 0
Model's Last Updated: December 09 2024

Introduction of opt125m-lora-billsum_3

Model Details of opt125m-lora-billsum_3

opt125m-lora-billsum_3

This model is a fine-tuned version of facebook/opt-125m on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 2.3043
Model description

More information needed

Intended uses & limitations

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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: 8
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 16
  • optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 1
  • num_epochs: 10
  • mixed_precision_training: Native AMP
Training results
Training Loss Epoch Step Validation Loss
No log 1.0 125 2.2764
No log 2.0 250 2.2876
No log 3.0 375 2.3012
1.3692 4.0 500 2.2974
1.3692 5.0 625 2.3014
1.3692 6.0 750 2.3048
1.3692 7.0 875 2.3049
1.251 8.0 1000 2.3026
1.251 9.0 1125 2.3060
1.251 10.0 1250 2.3043
Framework versions
  • PEFT 0.14.0
  • Transformers 4.47.0
  • Pytorch 2.5.1
  • Datasets 3.1.0
  • Tokenizers 0.21.0

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