ro-sentiment / README.md
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metadata
base_model: readerbench/RoBERT-base
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - precision
  - recall
  - f1
model-index:
  - name: ro-sentiment-03
    results: []

ro-sentiment-03

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

  • Loss: 0.3923
  • Accuracy: 0.8307
  • Precision: 0.8366
  • Recall: 0.8959
  • F1: 0.8652
  • F1 Weighted: 0.8287

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: 6e-05
  • train_batch_size: 64
  • eval_batch_size: 128
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.2
  • num_epochs: 10

Training results

Training Loss Epoch Step Validation Loss Accuracy Precision Recall F1 F1 Weighted
0.4198 1.0 1629 0.3983 0.8377 0.8791 0.8721 0.8756 0.8380
0.3861 2.0 3258 0.4312 0.8429 0.8963 0.8665 0.8812 0.8442
0.3189 3.0 4887 0.3923 0.8307 0.8366 0.8959 0.8652 0.8287

Framework versions

  • Transformers 4.31.0
  • Pytorch 2.0.1+cu118
  • Datasets 2.14.3
  • Tokenizers 0.13.3