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metadata
license: apache-2.0
tags:
  - generated_from_trainer
metrics:
  - f1
base_model: distilroberta-base
model-index:
  - name: distilroberta-base-finegrain
    results: []

distilroberta-base-finegrain

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

  • Loss: 0.3713
  • F1: 0.9129

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: 8
  • eval_batch_size: 8
  • seed: 42
  • distributed_type: multi-GPU
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 20

Training results

Training Loss Epoch Step Validation Loss F1
0.3944 1.0 844 0.3998 0.9163
0.3886 2.0 1688 0.4020 0.9163
0.3899 3.0 2532 0.3423 0.9163
0.4026 4.0 3376 0.3837 0.9163
0.3911 5.0 4220 0.3492 0.9163
0.3856 6.0 5064 0.3504 0.9163
0.4058 7.0 5908 0.3682 0.9163
0.4057 8.0 6752 0.3767 0.9163
0.3807 9.0 7596 0.3519 0.9163
0.394 10.0 8440 0.3603 0.9163
0.39 11.0 9284 0.3630 0.9163
0.3945 12.0 10128 0.3846 0.9163
0.3948 13.0 10972 0.3711 0.9163
0.3981 14.0 11816 0.3516 0.9163
0.4144 15.0 12660 0.3526 0.9163
0.3999 16.0 13504 0.3560 0.9163
0.376 17.0 14348 0.3671 0.9163
0.412 18.0 15192 0.3630 0.9163
0.389 19.0 16036 0.3669 0.9136
0.374 20.0 16880 0.3713 0.9129

Framework versions

  • Transformers 4.28.1
  • Pytorch 1.13.1+cu117
  • Datasets 2.12.0
  • Tokenizers 0.13.3