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

Text Classification
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PyTorch
bert
Generated from Trainer
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metadata
license: apache-2.0
base_model: bert-large-uncased
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: bert-large-uncased-sst-2-32-13-30
    results: []

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

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

  • Loss: 0.6452
  • Accuracy: 0.6719

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 0.7180 0.4688
No log 2.0 4 0.7071 0.4688
No log 3.0 6 0.6996 0.5469
No log 4.0 8 0.6827 0.5625
0.6456 5.0 10 0.6712 0.5469
0.6456 6.0 12 0.6542 0.6094
0.6456 7.0 14 0.6525 0.6719
0.6456 8.0 16 0.6535 0.6875
0.6456 9.0 18 0.6454 0.6406
0.4153 10.0 20 0.6414 0.625
0.4153 11.0 22 0.6470 0.6094
0.4153 12.0 24 0.6509 0.6094
0.4153 13.0 26 0.6489 0.6094
0.4153 14.0 28 0.6498 0.6094
0.238 15.0 30 0.6514 0.6094
0.238 16.0 32 0.6440 0.6562
0.238 17.0 34 0.6432 0.6719
0.238 18.0 36 0.6497 0.6719
0.238 19.0 38 0.6569 0.6406
0.1523 20.0 40 0.6636 0.6094
0.1523 21.0 42 0.6692 0.5781
0.1523 22.0 44 0.6740 0.5625
0.1523 23.0 46 0.6708 0.5625
0.1523 24.0 48 0.6632 0.6094
0.1187 25.0 50 0.6596 0.6406
0.1187 26.0 52 0.6560 0.6562
0.1187 27.0 54 0.6517 0.6719
0.1187 28.0 56 0.6482 0.6875
0.1187 29.0 58 0.6462 0.6875
0.09 30.0 60 0.6452 0.6719

Framework versions

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