Hugging Face's logo

TeamNL
/
NLP-at-home

Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
Inference Endpoints
Model card Files Metrics Community
NLP-at-home / README.md
TeamNL's picture
TeamNL
End of training
03ae269 verified
preview code
|
raw
history blame contribute delete
4.35 kB
metadata
license: apache-2.0
base_model: google-bert/bert-base-multilingual-uncased
tags:
  - generated_from_trainer
metrics:
  - f1
model-index:
  - name: NLP-at-home
    results: []

NLP-at-home

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

  • Loss: 1.1836
  • F1: 0.8284

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
  • num_epochs: 50

Training results

Training Loss Epoch Step Validation Loss F1
1.0833 1.0 24 0.6880 0.6592
0.5737 2.0 48 0.5213 0.8235
0.3165 3.0 72 0.5841 0.7939
0.2087 4.0 96 0.6425 0.7846
0.1377 5.0 120 0.7989 0.7536
0.0835 6.0 144 0.7516 0.8257
0.0963 7.0 168 0.7099 0.8243
0.0558 8.0 192 0.7994 0.7905
0.0389 9.0 216 0.7475 0.8494
0.057 10.0 240 0.7741 0.8265
0.0435 11.0 264 1.1178 0.7826
0.0458 12.0 288 0.9156 0.7847
0.033 13.0 312 0.9355 0.8198
0.0556 14.0 336 0.9090 0.8152
0.0139 15.0 360 0.9933 0.7950
0.0137 16.0 384 1.1050 0.7889
0.0173 17.0 408 1.1387 0.7836
0.0221 18.0 432 1.0860 0.8072
0.0206 19.0 456 1.0689 0.8120
0.0125 20.0 480 0.9927 0.8087
0.0034 21.0 504 1.1213 0.7919
0.0052 22.0 528 1.2096 0.7969
0.0005 23.0 552 1.1544 0.8132
0.0004 24.0 576 1.1947 0.8143
0.0017 25.0 600 1.2692 0.7957
0.0003 26.0 624 1.2705 0.7981
0.0004 27.0 648 1.4028 0.7617
0.0003 28.0 672 1.2183 0.8193
0.0038 29.0 696 1.2414 0.8106
0.0002 30.0 720 1.3012 0.8022
0.0008 31.0 744 1.1945 0.8120
0.0002 32.0 768 1.1859 0.8125
0.0002 33.0 792 1.1988 0.8078
0.0004 34.0 816 1.2846 0.8144
0.0016 35.0 840 1.2518 0.8121
0.0002 36.0 864 1.2062 0.8254
0.0002 37.0 888 1.2049 0.8197
0.0002 38.0 912 1.2056 0.8254
0.0001 39.0 936 1.2062 0.8254
0.0001 40.0 960 1.1666 0.8378
0.0001 41.0 984 1.1612 0.8378
0.0001 42.0 1008 1.1614 0.8378
0.0001 43.0 1032 1.1739 0.8277
0.0001 44.0 1056 1.1778 0.8277
0.0001 45.0 1080 1.1808 0.8284
0.0001 46.0 1104 1.1816 0.8284
0.0001 47.0 1128 1.1825 0.8284
0.0001 48.0 1152 1.1833 0.8284
0.0001 49.0 1176 1.1836 0.8284
0.0001 50.0 1200 1.1836 0.8284

Framework versions

  • Transformers 4.41.2
  • Pytorch 2.3.0+cu121
  • Datasets 2.18.0
  • Tokenizers 0.19.1