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mljn
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climate_un2

Text Classification
Transformers
Safetensors
distilbert
Generated from Trainer
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metadata
license: apache-2.0
base_model: distilbert-base-uncased
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: climate_un2
    results: []

climate_un2

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: 0.0929
  • Accuracy: 0.9860
  • F1 Macro: 0.9804
  • Accuracy Balanced: 0.9856
  • F1 Micro: 0.9860
  • Precision Macro: 0.9755
  • Recall Macro: 0.9856
  • Precision Micro: 0.9860
  • Recall Micro: 0.9860

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: 8
  • eval_batch_size: 80
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 16
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.06
  • num_epochs: 10

Training results

Training Loss Epoch Step Validation Loss Accuracy F1 Macro Accuracy Balanced F1 Micro Precision Macro Recall Macro Precision Micro Recall Micro
No log 1.0 167 0.0673 0.9851 0.9790 0.9796 0.9851 0.9783 0.9796 0.9851 0.9851
No log 2.0 334 0.0732 0.9834 0.9768 0.9839 0.9834 0.9702 0.9839 0.9834 0.9834
0.1178 3.0 501 0.0617 0.9860 0.9804 0.9856 0.9860 0.9755 0.9856 0.9860 0.9860
0.1178 4.0 668 0.0593 0.9886 0.9840 0.9873 0.9886 0.9809 0.9873 0.9886 0.9886
0.1178 5.0 835 0.0822 0.9843 0.9780 0.9844 0.9843 0.9720 0.9844 0.9843 0.9843
0.0088 6.0 1002 0.0810 0.9878 0.9829 0.9880 0.9878 0.9779 0.9880 0.9878 0.9878
0.0088 7.0 1169 0.0904 0.9860 0.9804 0.9856 0.9860 0.9755 0.9856 0.9860 0.9860
0.0088 8.0 1336 0.0927 0.9860 0.9804 0.9856 0.9860 0.9755 0.9856 0.9860 0.9860
0.0006 9.0 1503 0.0936 0.9860 0.9805 0.9869 0.9860 0.9744 0.9869 0.9860 0.9860
0.0006 10.0 1670 0.0929 0.9860 0.9804 0.9856 0.9860 0.9755 0.9856 0.9860 0.9860

Framework versions

  • Transformers 4.35.1
  • Pytorch 2.1.0+cu118
  • Datasets 2.14.7
  • Tokenizers 0.14.1