rating-classifier / README.md
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data-silence/rating-classifier
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metadata
license: apache-2.0
base_model: bert-base-uncased
tags:
  - generated_from_trainer
metrics:
  - f1
  - accuracy
  - precision
  - recall
model-index:
  - name: rating-classifier
    results: []

rating-classifier

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

  • F1: 0.6729
  • Loss: 0.8373
  • Accuracy: 0.6710
  • Precision: 0.6774
  • Recall: 0.6710

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: 16
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • num_epochs: 5

Training results

Training Loss Epoch Step F1 Validation Loss Accuracy Precision Recall
1.0326 1.0 984 0.6354 0.8096 0.6707 0.6383 0.6707
0.6801 2.0 1968 0.6668 0.7508 0.6888 0.6667 0.6888
0.5313 3.0 2952 0.6729 0.8373 0.6710 0.6774 0.6710
0.3895 4.0 3936 0.6678 0.9705 0.6730 0.6649 0.6730
0.2857 5.0 4920 0.6708 1.0989 0.6745 0.6684 0.6745

Framework versions

  • Transformers 4.42.4
  • Pytorch 2.3.1+cu121
  • Datasets 2.21.0
  • Tokenizers 0.19.1