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metadata
license: mit
tags:
  - generated_from_trainer
metrics:
  - precision
  - recall
  - f1
  - accuracy
model-index:
  - name: roberta-large-condaqa-neg-tag-token-classifier
    results: []

roberta-large-condaqa-neg-tag-token-classifier

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

  • Loss: 0.0268
  • Precision: 0.0
  • Recall: 0.0
  • F1: 0.0
  • Accuracy: 0.9899

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: 5e-05
  • train_batch_size: 256
  • eval_batch_size: 32
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 6.0

Training results

Training Loss Epoch Step Validation Loss Precision Recall F1 Accuracy
No log 1.0 4 0.1526 0.0 0.0 0.0 0.9588
No log 2.0 8 0.0875 0.0 0.0 0.0 0.9588
No log 3.0 12 0.0396 0.0 0.0 0.0 0.9877
No log 4.0 16 0.0322 0.0 0.0 0.0 0.9899
No log 5.0 20 0.0270 0.0 0.0 0.0 0.9906
No log 6.0 24 0.0268 0.0 0.0 0.0 0.9899

Framework versions

  • Transformers 4.25.0.dev0
  • Pytorch 1.10.1
  • Datasets 2.6.1
  • Tokenizers 0.13.1