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gpt2-NER-favsbot

Token Classification
Transformers
PyTorch
gpt2
generated_from_trainer
Eval Results
Inference Endpoints
text-generation-inference
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metadata
license: mit
tags:
  - generated_from_trainer
datasets:
  - favsbot
metrics:
  - precision
  - recall
  - f1
  - accuracy
model-index:
  - name: gpt2-NER-favsbot
    results:
      - task:
          name: Token Classification
          type: token-classification
        dataset:
          name: favsbot
          type: favsbot
          config: default
          split: train
          args: default
        metrics:
          - name: Precision
            type: precision
            value: 0.3782051282051282
          - name: Recall
            type: recall
            value: 0.3277777777777778
          - name: F1
            type: f1
            value: 0.3511904761904762
          - name: Accuracy
            type: accuracy
            value: 0.5597189695550351

gpt2-NER-favsbot

This model is a fine-tuned version of gpt2 on the favsbot dataset. It achieves the following results on the evaluation set:

  • Loss: 1.5146
  • Precision: 0.3782
  • Recall: 0.3278
  • F1: 0.3512
  • Accuracy: 0.5597

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: 1.5e-05
  • train_batch_size: 16
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 20

Training results

Training Loss Epoch Step Validation Loss Precision Recall F1 Accuracy
No log 1.0 4 4.0808 0.0630 0.0444 0.0521 0.0773
No log 2.0 8 3.5205 0.0946 0.0778 0.0854 0.1077
No log 3.0 12 3.0413 0.0909 0.0722 0.0805 0.2084
No log 4.0 16 2.6817 0.0615 0.0444 0.0516 0.2740
No log 5.0 20 2.4227 0.1140 0.0722 0.0884 0.3560
No log 6.0 24 2.2422 0.1382 0.0944 0.1122 0.3770
No log 7.0 28 2.0941 0.1654 0.1222 0.1406 0.3864
No log 8.0 32 1.9726 0.2344 0.1667 0.1948 0.4309
No log 9.0 36 1.8916 0.2925 0.1722 0.2168 0.4543
No log 10.0 40 1.8321 0.31 0.1722 0.2214 0.4660
No log 11.0 44 1.7697 0.2957 0.1889 0.2305 0.4707
No log 12.0 48 1.7087 0.3228 0.2278 0.2671 0.4965
No log 13.0 52 1.6551 0.3485 0.2556 0.2949 0.5152
No log 14.0 56 1.6136 0.3219 0.2611 0.2883 0.5176
No log 15.0 60 1.5819 0.3510 0.2944 0.3202 0.5363
No log 16.0 64 1.5575 0.3506 0.3 0.3234 0.5410
No log 17.0 68 1.5394 0.3529 0.3 0.3243 0.5433
No log 18.0 72 1.5265 0.3791 0.3222 0.3483 0.5574
No log 19.0 76 1.5180 0.3766 0.3222 0.3473 0.5574
No log 20.0 80 1.5146 0.3782 0.3278 0.3512 0.5597

Framework versions

  • Transformers 4.21.1
  • Pytorch 1.12.1
  • Datasets 2.4.0
  • Tokenizers 0.12.1