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metadata
license: apache-2.0
base_model: bert-base-uncased
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: Raffel_bert_emotion_classification
    results: []

Raffel_bert_emotion_classification

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: 0.3423
  • Accuracy: 0.9596

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: 4e-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
  • num_epochs: 20

Training results

Training Loss Epoch Step Validation Loss Accuracy
No log 1.0 167 0.1212 0.9579
No log 2.0 334 0.1362 0.9596
0.1622 3.0 501 0.2034 0.9596
0.1622 4.0 668 0.2035 0.9630
0.1622 5.0 835 0.2153 0.9630
0.017 6.0 1002 0.2010 0.9613
0.017 7.0 1169 0.2718 0.9579
0.017 8.0 1336 0.2641 0.9613
0.0099 9.0 1503 0.2524 0.9613
0.0099 10.0 1670 0.2918 0.9579
0.0099 11.0 1837 0.2749 0.9562
0.0029 12.0 2004 0.3133 0.9562
0.0029 13.0 2171 0.2952 0.9579
0.0029 14.0 2338 0.3334 0.9596
0.0022 15.0 2505 0.3286 0.9596
0.0022 16.0 2672 0.3340 0.9596
0.0022 17.0 2839 0.3344 0.9596
0.0013 18.0 3006 0.3395 0.9596
0.0013 19.0 3173 0.3423 0.9596
0.0013 20.0 3340 0.3423 0.9596

Framework versions

  • Transformers 4.34.1
  • Pytorch 2.1.0+cu118
  • Datasets 2.14.6
  • Tokenizers 0.14.1