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metadata
license: mit
tags:
  - generated_from_trainer
metrics:
  - precision
  - recall
  - f1
  - accuracy
model-index:
  - name: roberta_large-chunking_0715_v0
    results: []

roberta_large-chunking_0715_v0

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

  • Loss: 0.3602
  • Precision: 0.3182
  • Recall: 0.2213
  • F1: 0.2610
  • Accuracy: 0.8681

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: 1e-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: 5

Training results

Training Loss Epoch Step Validation Loss Precision Recall F1 Accuracy
No log 1.0 63 0.4019 0.5525 0.0824 0.1434 0.8748
No log 2.0 126 0.3614 0.4887 0.1517 0.2315 0.8747
No log 3.0 189 0.3569 0.4484 0.1638 0.2399 0.8744
No log 4.0 252 0.3581 0.3685 0.1909 0.2515 0.8719
No log 5.0 315 0.3602 0.3182 0.2213 0.2610 0.8681

Framework versions

  • Transformers 4.20.1
  • Pytorch 1.12.0+cu113
  • Datasets 2.3.2
  • Tokenizers 0.12.1