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MiniLMv2-L12-H384-distilled-from-RoBERTa-Large-finetuned-clinc

This model is a fine-tuned version of nreimers/MiniLMv2-L12-H384-distilled-from-RoBERTa-Large on the clinc_oos dataset. It achieves the following results on the evaluation set:

  • Loss: 1.5252
  • Accuracy: 0.9319

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: 0.0001
  • train_batch_size: 256
  • eval_batch_size: 256
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 10

Training results

Training Loss Epoch Step Validation Loss Accuracy
No log 1.0 60 4.6555 0.1887
No log 2.0 120 3.8771 0.4784
No log 3.0 180 3.2507 0.7352
3.9668 4.0 240 2.7445 0.8365
3.9668 5.0 300 2.3475 0.8865
3.9668 6.0 360 2.0370 0.8926
3.9668 7.0 420 1.8099 0.9145
2.0924 8.0 480 1.6433 0.9190
2.0924 9.0 540 1.5563 0.9281
2.0924 10.0 600 1.5252 0.9319

Framework versions

  • Transformers 4.11.3
  • Pytorch 1.11.0
  • Datasets 1.16.1
  • Tokenizers 0.10.3
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Dataset used to train optimum/MiniLMv2-L12-H384-finetuned-clinc

Evaluation results