movieHunt4-ner / README.md
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metadata
license: apache-2.0
tags:
  - generated_from_trainer
metrics:
  - precision
  - recall
  - f1
  - accuracy
model-index:
  - name: movieHunt4-ner
    results: []

movieHunt4-ner

This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0005
  • Precision: 1.0
  • Recall: 1.0
  • F1: 1.0
  • Accuracy: 1.0

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: 32
  • eval_batch_size: 32
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 30

Training results

Training Loss Epoch Step Validation Loss Precision Recall F1 Accuracy
No log 1.0 48 0.0284 0.9959 0.9959 0.9959 0.9974
No log 2.0 96 0.0060 1.0 1.0 1.0 1.0
No log 3.0 144 0.0034 1.0 1.0 1.0 1.0
No log 4.0 192 0.0025 1.0 1.0 1.0 1.0
No log 5.0 240 0.0020 1.0 1.0 1.0 1.0
No log 6.0 288 0.0016 1.0 1.0 1.0 1.0
No log 7.0 336 0.0014 1.0 1.0 1.0 1.0
No log 8.0 384 0.0012 1.0 1.0 1.0 1.0
No log 9.0 432 0.0011 1.0 1.0 1.0 1.0
No log 10.0 480 0.0010 1.0 1.0 1.0 1.0
0.0168 11.0 528 0.0009 1.0 1.0 1.0 1.0
0.0168 12.0 576 0.0009 1.0 1.0 1.0 1.0
0.0168 13.0 624 0.0008 1.0 1.0 1.0 1.0
0.0168 14.0 672 0.0008 1.0 1.0 1.0 1.0
0.0168 15.0 720 0.0008 1.0 1.0 1.0 1.0
0.0168 16.0 768 0.0007 1.0 1.0 1.0 1.0
0.0168 17.0 816 0.0007 1.0 1.0 1.0 1.0
0.0168 18.0 864 0.0007 1.0 1.0 1.0 1.0
0.0168 19.0 912 0.0006 1.0 1.0 1.0 1.0
0.0168 20.0 960 0.0006 1.0 1.0 1.0 1.0
0.0014 21.0 1008 0.0006 1.0 1.0 1.0 1.0
0.0014 22.0 1056 0.0006 1.0 1.0 1.0 1.0
0.0014 23.0 1104 0.0006 1.0 1.0 1.0 1.0
0.0014 24.0 1152 0.0006 1.0 1.0 1.0 1.0
0.0014 25.0 1200 0.0005 1.0 1.0 1.0 1.0
0.0014 26.0 1248 0.0005 1.0 1.0 1.0 1.0
0.0014 27.0 1296 0.0005 1.0 1.0 1.0 1.0
0.0014 28.0 1344 0.0005 1.0 1.0 1.0 1.0
0.0014 29.0 1392 0.0005 1.0 1.0 1.0 1.0
0.0014 30.0 1440 0.0005 1.0 1.0 1.0 1.0

Framework versions

  • Transformers 4.21.0
  • Pytorch 1.12.0+cu113
  • Datasets 2.4.0
  • Tokenizers 0.12.1