jayanta / roberta-fine-sentiment-hineng-concat

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Total runs: 13
24-hour runs: 0
7-day runs: 2
30-day runs: -9
Model's Last Updated: September 19 2022
text-classification

Introduction of roberta-fine-sentiment-hineng-concat

Model Details of roberta-fine-sentiment-hineng-concat

roberta-fine-sentiment-hineng-concat

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

  • Loss: 1.1126
  • Accuracy: 0.8669
  • Precision: 0.8667
  • Recall: 0.8669
  • F1: 0.8668
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: 4
  • eval_batch_size: 4
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 8
Training results
Training Loss Epoch Step Validation Loss Accuracy Precision Recall F1
0.5814 1.0 4293 0.6920 0.8249 0.8304 0.8249 0.8257
0.5169 2.0 8586 0.5919 0.8459 0.8499 0.8459 0.8465
0.4274 3.0 12879 0.7775 0.8512 0.8513 0.8512 0.8504
0.3246 4.0 17172 0.7757 0.8522 0.8593 0.8522 0.8528
0.22 5.0 21465 0.9306 0.8574 0.8574 0.8574 0.8574
0.1226 6.0 25758 0.9663 0.8627 0.8632 0.8627 0.8628
0.085 7.0 30051 1.0266 0.8653 0.8651 0.8653 0.8651
0.0713 8.0 34344 1.1126 0.8669 0.8667 0.8669 0.8668
Framework versions
  • Transformers 4.22.1
  • Pytorch 1.12.1+cu113
  • Datasets 2.4.0
  • Tokenizers 0.12.1

Runs of jayanta roberta-fine-sentiment-hineng-concat on huggingface.co

13
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0
24-hour runs
2
3-day runs
2
7-day runs
-9
30-day runs

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