my_fancy_model / README.md
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metadata
license: apache-2.0
base_model: distilbert/distilbert-base-uncased
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - recall
  - precision
model-index:
  - name: my_fancy_model
    results: []

my_fancy_model

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

  • Loss: 0.6695
  • Accuracy: 0.65
  • Recall: 0.5
  • Precision: 0.325

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: 16
  • eval_batch_size: 8
  • 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 Accuracy Recall Precision
No log 1.0 7 0.7025 0.65 0.5 0.325
No log 2.0 14 0.6968 0.65 0.5 0.325
No log 3.0 21 0.8017 0.65 0.5 0.325
No log 4.0 28 0.6836 0.65 0.5 0.325
No log 5.0 35 0.6695 0.65 0.5 0.325

Framework versions

  • Transformers 4.38.2
  • Pytorch 2.2.1
  • Datasets 2.18.0
  • Tokenizers 0.15.2