Hugging Face's logo

genki10
/
ASAP_FineTuningBERT_AugV5_k2_task1_organization_fold0

Text Classification
Transformers
Safetensors
bert
Generated from Trainer
Inference Endpoints
Model card Files Community
ASAP_FineTuningBERT_AugV5_k2_task1_organization_fold0 / README.md
genki10's picture
genki10
Training in progress, step 100
b0ab3a0 verified
preview code
|
raw
history blame
5.33 kB
metadata
library_name: transformers
license: apache-2.0
base_model: bert-base-uncased
tags:
  - generated_from_trainer
model-index:
  - name: ASAP_FineTuningBERT_AugV5_k1_task1_organization_fold4
    results: []

ASAP_FineTuningBERT_AugV5_k1_task1_organization_fold4

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

  • Loss: 0.5758
  • Qwk: 0.6718
  • Mse: 0.5758
  • Rmse: 0.7588

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: 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: 100

Training results

Training Loss Epoch Step Validation Loss Qwk Mse Rmse
No log 2.0 2 9.7683 0.0018 9.7683 3.1254
No log 4.0 4 8.2498 0.0018 8.2498 2.8722
No log 6.0 6 6.8328 0.0 6.8328 2.6140
No log 8.0 8 5.3375 0.0329 5.3375 2.3103
8.9731 10.0 10 4.3556 0.0118 4.3556 2.0870
8.9731 12.0 12 3.5608 0.0040 3.5608 1.8870
8.9731 14.0 14 2.8777 0.0040 2.8777 1.6964
8.9731 16.0 16 2.3505 0.1010 2.3505 1.5331
8.9731 18.0 18 1.9685 0.1264 1.9685 1.4030
4.3314 20.0 20 1.6149 0.0734 1.6149 1.2708
4.3314 22.0 22 1.4079 0.1092 1.4079 1.1865
4.3314 24.0 24 1.1654 0.0975 1.1654 1.0796
4.3314 26.0 26 0.9621 0.0975 0.9621 0.9809
4.3314 28.0 28 1.0460 0.1775 1.0460 1.0228
2.3195 30.0 30 0.7254 0.4930 0.7254 0.8517
2.3195 32.0 32 0.6288 0.5308 0.6288 0.7930
2.3195 34.0 34 0.7271 0.5327 0.7271 0.8527
2.3195 36.0 36 0.5334 0.5459 0.5334 0.7303
2.3195 38.0 38 0.5264 0.5264 0.5264 0.7256
1.2151 40.0 40 0.5444 0.6055 0.5444 0.7378
1.2151 42.0 42 0.4974 0.5838 0.4974 0.7053
1.2151 44.0 44 0.4992 0.5834 0.4992 0.7065
1.2151 46.0 46 0.4907 0.6217 0.4907 0.7005
1.2151 48.0 48 0.4903 0.6602 0.4903 0.7002
0.6065 50.0 50 0.4976 0.6520 0.4976 0.7054
0.6065 52.0 52 0.4928 0.6757 0.4928 0.7020
0.6065 54.0 54 0.5738 0.6383 0.5738 0.7575
0.6065 56.0 56 0.5469 0.6828 0.5469 0.7395
0.6065 58.0 58 0.5523 0.6760 0.5523 0.7432
0.3084 60.0 60 0.5803 0.6420 0.5803 0.7618
0.3084 62.0 62 0.6608 0.6124 0.6608 0.8129
0.3084 64.0 64 0.5481 0.6893 0.5481 0.7404
0.3084 66.0 66 0.5452 0.6779 0.5452 0.7384
0.3084 68.0 68 0.6938 0.6277 0.6938 0.8329
0.1723 70.0 70 0.7560 0.6070 0.7560 0.8695
0.1723 72.0 72 0.5880 0.6867 0.5880 0.7668
0.1723 74.0 74 0.5626 0.6901 0.5626 0.7501
0.1723 76.0 76 0.6318 0.6317 0.6318 0.7948
0.1723 78.0 78 0.6981 0.6187 0.6981 0.8355
0.1229 80.0 80 0.6227 0.6372 0.6227 0.7891
0.1229 82.0 82 0.6047 0.6486 0.6047 0.7776
0.1229 84.0 84 0.6171 0.6511 0.6171 0.7855
0.1229 86.0 86 0.6257 0.6465 0.6257 0.7910
0.1229 88.0 88 0.6828 0.6261 0.6828 0.8263
0.0736 90.0 90 0.6638 0.6255 0.6638 0.8147
0.0736 92.0 92 0.5854 0.6629 0.5854 0.7651
0.0736 94.0 94 0.5649 0.6745 0.5649 0.7516
0.0736 96.0 96 0.5690 0.6734 0.5690 0.7543
0.0736 98.0 98 0.5707 0.6734 0.5707 0.7554
0.0687 100.0 100 0.5758 0.6718 0.5758 0.7588

Framework versions

  • Transformers 4.44.2
  • Pytorch 2.4.1+cu121
  • Datasets 3.2.0
  • Tokenizers 0.19.1