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distilbert-base-multilingual-cased-sentiment

This model is a fine-tuned version of distilbert-base-multilingual-cased on the amazon_reviews_multi dataset. It achieves the following results on the evaluation set:

  • Loss: 0.5842
  • Accuracy: 0.7648
  • F1: 0.7648

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: 16
  • seed: 33
  • distributed_type: sagemaker_data_parallel
  • num_devices: 8
  • total_train_batch_size: 128
  • total_eval_batch_size: 128
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • num_epochs: 5
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Accuracy F1
0.6405 0.53 5000 0.5826 0.7498 0.7498
0.5698 1.07 10000 0.5686 0.7612 0.7612
0.5286 1.6 15000 0.5593 0.7636 0.7636
0.5141 2.13 20000 0.5842 0.7648 0.7648
0.4763 2.67 25000 0.5736 0.7637 0.7637
0.4549 3.2 30000 0.6027 0.7593 0.7593
0.4231 3.73 35000 0.6017 0.7552 0.7552
0.3965 4.27 40000 0.6489 0.7551 0.7551
0.3744 4.8 45000 0.6426 0.7534 0.7534

Framework versions

  • Transformers 4.12.3
  • Pytorch 1.9.1
  • Datasets 1.15.1
  • Tokenizers 0.10.3
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Dataset used to train philschmid/distilbert-base-multilingual-cased-sentiment

Evaluation results