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FPB_finetuned_v1

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bert
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finetuned on balanced data
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metadata
license: apache-2.0
base_model: bert-base-uncased
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - f1
  - precision
  - recall
model-index:
  - name: FPB_finetuned_v1
    results: []

FPB_finetuned_v1

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

  • Loss: 0.4649
  • Accuracy: 0.9303
  • F1: 0.9303
  • Precision: 0.9303
  • Recall: 0.9303

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: 0.0001
  • train_batch_size: 64
  • eval_batch_size: 64
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 1000
  • num_epochs: 20

Training results

Training Loss Epoch Step Validation Loss Accuracy F1 Precision Recall
0.7905 1.0 97 0.6913 0.7504 0.7471 0.7458 0.7504
0.3516 2.0 194 0.3914 0.8476 0.8480 0.8517 0.8476
0.2545 3.0 291 0.3302 0.8882 0.8870 0.8911 0.8882
0.1225 4.0 388 0.3488 0.8723 0.8730 0.8801 0.8723
0.0674 5.0 485 0.3910 0.8970 0.8961 0.8963 0.8970
0.0458 6.0 582 0.4545 0.9028 0.9022 0.9036 0.9028
0.0963 7.0 679 0.3467 0.9100 0.9100 0.9104 0.9100
0.0781 8.0 776 0.4528 0.8999 0.8991 0.8996 0.8999
0.0961 9.0 873 0.3966 0.9042 0.9049 0.9091 0.9042
0.0643 10.0 970 0.3486 0.9158 0.9159 0.9160 0.9158
0.0521 11.0 1067 0.5745 0.8955 0.8931 0.9030 0.8955
0.0162 12.0 1164 0.4968 0.9042 0.9047 0.9070 0.9042
0.0106 13.0 1261 0.4925 0.9158 0.9161 0.9171 0.9158
0.0056 14.0 1358 0.5128 0.9129 0.9126 0.9149 0.9129
0.0116 15.0 1455 0.4791 0.9202 0.9199 0.9197 0.9202
0.0004 16.0 1552 0.4417 0.9216 0.9214 0.9218 0.9216
0.0121 17.0 1649 0.4378 0.9202 0.9199 0.9205 0.9202
0.0003 18.0 1746 0.4624 0.9245 0.9245 0.9247 0.9245
0.0001 19.0 1843 0.4697 0.9274 0.9275 0.9277 0.9274
0.0001 20.0 1940 0.4649 0.9303 0.9303 0.9303 0.9303

Framework versions

  • Transformers 4.37.2
  • Pytorch 2.1.0+cu121
  • Tokenizers 0.15.2