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metadata
license: apache-2.0
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: distilbert-base-uncased__sst2__train-16-6
    results: []

distilbert-base-uncased__sst2__train-16-6

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

  • Loss: 0.8356
  • Accuracy: 0.6480

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: 50
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.6978 1.0 7 0.6807 0.4286
0.6482 2.0 14 0.6775 0.4286
0.6051 3.0 21 0.6623 0.5714
0.486 4.0 28 0.6710 0.5714
0.4612 5.0 35 0.5325 0.7143
0.2233 6.0 42 0.4992 0.7143
0.1328 7.0 49 0.4753 0.7143
0.0905 8.0 56 0.2416 1.0
0.0413 9.0 63 0.2079 1.0
0.0356 10.0 70 0.2234 0.8571
0.0217 11.0 77 0.2639 0.8571
0.0121 12.0 84 0.2977 0.8571
0.0105 13.0 91 0.3468 0.8571
0.0085 14.0 98 0.3912 0.8571
0.0077 15.0 105 0.4000 0.8571
0.0071 16.0 112 0.4015 0.8571
0.0078 17.0 119 0.3865 0.8571
0.0059 18.0 126 0.3603 0.8571
0.0051 19.0 133 0.3231 0.8571

Framework versions

  • Transformers 4.15.0
  • Pytorch 1.10.2+cu102
  • Datasets 1.18.2
  • Tokenizers 0.10.3