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distilbert-base-uncased-finetuned-ner

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metadata
license: apache-2.0
base_model: distilbert-base-uncased
tags:
  - generated_from_trainer
metrics:
  - precision
  - recall
  - f1
  - accuracy
model-index:
  - name: distilbert-base-uncased-finetuned-ner
    results: []

distilbert-base-uncased-finetuned-ner

This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4181
  • Precision: 0.6106
  • Recall: 0.6615
  • F1: 0.635
  • Accuracy: 0.9189

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: 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: 30

Training results

Training Loss Epoch Step Validation Loss Precision Recall F1 Accuracy
No log 1.0 23 0.3610 0.4795 0.6094 0.5367 0.9045
No log 2.0 46 0.3516 0.5330 0.5885 0.5594 0.9141
No log 3.0 69 0.3591 0.5346 0.6042 0.5672 0.9147
No log 4.0 92 0.3602 0.5226 0.6615 0.5839 0.9129
No log 5.0 115 0.3706 0.5315 0.6146 0.5700 0.9123
No log 6.0 138 0.3652 0.5631 0.6042 0.5829 0.9165
No log 7.0 161 0.3618 0.5640 0.6198 0.5906 0.9153
No log 8.0 184 0.3680 0.5755 0.6354 0.6040 0.9165
No log 9.0 207 0.3782 0.5789 0.6302 0.6035 0.9183
No log 10.0 230 0.3926 0.6020 0.6302 0.6158 0.9189
No log 11.0 253 0.3816 0.5845 0.6667 0.6229 0.9171
No log 12.0 276 0.3811 0.5942 0.6406 0.6165 0.9195
No log 13.0 299 0.3857 0.5885 0.6406 0.6135 0.9189
No log 14.0 322 0.3966 0.5714 0.6458 0.6064 0.9141
No log 15.0 345 0.3927 0.6019 0.6615 0.6303 0.9183
No log 16.0 368 0.3955 0.5907 0.6615 0.6241 0.9165
No log 17.0 391 0.4124 0.5931 0.6302 0.6111 0.9171
No log 18.0 414 0.4112 0.5733 0.6719 0.6187 0.9135
No log 19.0 437 0.4177 0.5829 0.6406 0.6104 0.9159
No log 20.0 460 0.4100 0.6028 0.6719 0.6355 0.9159
No log 21.0 483 0.4159 0.5869 0.6510 0.6173 0.9165
0.0279 22.0 506 0.4100 0.5853 0.6615 0.6210 0.9153
0.0279 23.0 529 0.4127 0.6172 0.6719 0.6434 0.9189
0.0279 24.0 552 0.4074 0.5945 0.6719 0.6308 0.9153
0.0279 25.0 575 0.4056 0.5909 0.6771 0.6311 0.9165
0.0279 26.0 598 0.4079 0.5740 0.6667 0.6169 0.9153
0.0279 27.0 621 0.4184 0.6117 0.6562 0.6332 0.9189
0.0279 28.0 644 0.4177 0.6165 0.6615 0.6382 0.9195
0.0279 29.0 667 0.4178 0.6106 0.6615 0.635 0.9189
0.0279 30.0 690 0.4181 0.6106 0.6615 0.635 0.9189

Framework versions

  • Transformers 4.36.2
  • Pytorch 2.1.2+cu118
  • Datasets 2.16.0
  • Tokenizers 0.15.0