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models
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metadata
license: apache-2.0
base_model: distilbert-base-uncased
tags:
  - generated_from_trainer
metrics:
  - f1
  - accuracy
  - recall
  - precision
model-index:
  - name: distil_bert_tuned_2
    results: []

distil_bert_tuned_2

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

  • Loss: 0.5698
  • F1: 0.8253
  • Accuracy: 0.7816
  • Recall: 0.7088
  • Precision: 0.2347

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: 64
  • eval_batch_size: 64
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 3

Training results

Training Loss Epoch Step Validation Loss F1 Accuracy Recall Precision
0.5698 1.0 605 0.5390 0.8419 0.8063 0.6549 0.2502
0.5006 2.0 1210 0.5075 0.8052 0.7527 0.7599 0.2192
0.4526 3.0 1815 0.5698 0.8253 0.7816 0.7088 0.2347

Framework versions

  • Transformers 4.33.3
  • Pytorch 2.0.1+cpu
  • Datasets 2.14.5
  • Tokenizers 0.13.3