Hugging Face's logo

simonycl
/
bert-base-uncased-sst-2-32-13-30

Text Classification
Transformers
PyTorch
bert
Generated from Trainer
Inference Endpoints
Model card Files Community
bert-base-uncased-sst-2-32-13-30 / README.md
simonycl's picture
simonycl
update model card README.md
4988b60
preview code
|
raw
history blame contribute delete
3.22 kB
metadata
license: apache-2.0
base_model: bert-base-uncased
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: bert-base-uncased-sst-2-32-13-30
    results: []

bert-base-uncased-sst-2-32-13-30

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: 0.5572
  • Accuracy: 0.75

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: 32
  • eval_batch_size: 32
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 5
  • num_epochs: 30

Training results

Training Loss Epoch Step Validation Loss Accuracy
No log 1.0 2 0.6997 0.4375
No log 2.0 4 0.6973 0.4375
No log 3.0 6 0.6912 0.5781
No log 4.0 8 0.6876 0.5
0.6783 5.0 10 0.6843 0.5312
0.6783 6.0 12 0.6800 0.5781
0.6783 7.0 14 0.6738 0.5938
0.6783 8.0 16 0.6662 0.6562
0.6783 9.0 18 0.6573 0.6562
0.5945 10.0 20 0.6496 0.7031
0.5945 11.0 22 0.6427 0.7188
0.5945 12.0 24 0.6343 0.7188
0.5945 13.0 26 0.6270 0.7031
0.5945 14.0 28 0.6218 0.6875
0.4805 15.0 30 0.6166 0.6875
0.4805 16.0 32 0.6110 0.7188
0.4805 17.0 34 0.6046 0.7344
0.4805 18.0 36 0.5972 0.7344
0.4805 19.0 38 0.5895 0.7344
0.3522 20.0 40 0.5823 0.75
0.3522 21.0 42 0.5767 0.7344
0.3522 22.0 44 0.5708 0.7344
0.3522 23.0 46 0.5667 0.7344
0.3522 24.0 48 0.5637 0.7344
0.2697 25.0 50 0.5616 0.7344
0.2697 26.0 52 0.5603 0.7344
0.2697 27.0 54 0.5592 0.7344
0.2697 28.0 56 0.5582 0.75
0.2697 29.0 58 0.5574 0.75
0.2363 30.0 60 0.5572 0.75

Framework versions

  • Transformers 4.32.0.dev0
  • Pytorch 2.0.1+cu118
  • Datasets 2.4.0
  • Tokenizers 0.13.3