grace-pro / aligned_source_5e-5

huggingface.co
Total runs: 8
24-hour runs: 0
7-day runs: 0
30-day runs: 3
Model's Last Updated: August 07 2023
token-classification

Introduction of aligned_source_5e-5

Model Details of aligned_source_5e-5

aligned_source_5e-5

This model is a fine-tuned version of Davlan/afro-xlmr-base on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.1076
  • Precision: 0.3551
  • Recall: 0.2680
  • F1: 0.3054
  • Accuracy: 0.9711
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: 5e-05
  • train_batch_size: 16
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 5
Training results
Training Loss Epoch Step Validation Loss Precision Recall F1 Accuracy
0.1109 1.0 1016 0.0905 0.3897 0.0842 0.1385 0.9745
0.0994 2.0 2032 0.0896 0.3712 0.2191 0.2756 0.9729
0.0861 3.0 3048 0.0936 0.3626 0.2567 0.3006 0.9718
0.0698 4.0 4064 0.0989 0.3665 0.2639 0.3068 0.9718
0.0594 5.0 5080 0.1076 0.3551 0.2680 0.3054 0.9711
Framework versions
  • Transformers 4.31.0
  • Pytorch 2.0.1+cu118
  • Datasets 2.14.3
  • Tokenizers 0.13.3

Runs of grace-pro aligned_source_5e-5 on huggingface.co

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

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aligned_source_5e-5 install

aligned_source_5e-5 is an open source model from GitHub that offers a free installation service, and any user can find aligned_source_5e-5 on GitHub to install. At the same time, huggingface.co provides the effect of aligned_source_5e-5 install, users can directly use aligned_source_5e-5 installed effect in huggingface.co for debugging and trial. It also supports api for free installation.

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