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MiniLMv2-L12-H384-distilled-from-RoBERTa-Large-distilled-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: 0.3479
  • Accuracy: 0.94

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 0.8171 0.2490
No log 2.0 120 0.7039 0.6568
No log 3.0 180 0.6067 0.7932
0.7269 4.0 240 0.5270 0.8674
0.7269 5.0 300 0.4659 0.9010
0.7269 6.0 360 0.4201 0.9194
0.7269 7.0 420 0.3867 0.9352
0.4426 8.0 480 0.3649 0.9352
0.4426 9.0 540 0.3520 0.9403
0.4426 10.0 600 0.3479 0.94

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-distilled-finetuned-clinc

Evaluation results