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metadata
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - f1
  - precision
  - recall
model-index:
  - name: >-
      distilrubert-tiny-cased-conversational-v1_single_finetuned_empathy_classifier
    results: []

distilrubert-tiny-cased-conversational-v1_single_finetuned_empathy_classifier

This model is a fine-tuned version of DeepPavlov/distilrubert-tiny-cased-conversational-v1 on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 1.0183
  • Accuracy: 0.6218
  • F1: 0.6262
  • Precision: 0.6318
  • Recall: 0.6218

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: 64
  • eval_batch_size: 64
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-06
  • lr_scheduler_type: linear
  • num_epochs: 20

Training results

Training Loss Epoch Step Validation Loss Accuracy F1 Precision Recall
1.0456 1.0 9 0.9718 0.4958 0.4197 0.6526 0.4958
0.9042 2.0 18 0.8920 0.5882 0.5769 0.5784 0.5882
0.7923 3.0 27 0.8427 0.6134 0.5861 0.5935 0.6134
0.7544 4.0 36 0.8400 0.6387 0.6234 0.6344 0.6387
0.6675 5.0 45 0.8410 0.6303 0.6095 0.6184 0.6303
0.6091 6.0 54 0.9095 0.6050 0.6041 0.6396 0.6050
0.6279 7.0 63 0.8596 0.6723 0.6692 0.6725 0.6723
0.4968 8.0 72 0.8725 0.6303 0.6274 0.6253 0.6303
0.4459 9.0 81 0.9120 0.6387 0.6395 0.6426 0.6387
0.4122 10.0 90 0.9478 0.6303 0.6262 0.6248 0.6303
0.3244 11.0 99 0.9746 0.6387 0.6375 0.6381 0.6387
0.3535 12.0 108 1.0183 0.6218 0.6262 0.6318 0.6218

Framework versions

  • Transformers 4.20.1
  • Pytorch 1.12.0+cu113
  • Datasets 2.4.0
  • Tokenizers 0.12.1