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metadata
license: apache-2.0
base_model: distilbert/distilbert-base-multilingual-cased
tags:
  - generated_from_trainer
model-index:
  - name: distilbert-base-multilingual-cased_regression_finetuned_dcard
    results: []

distilbert-base-multilingual-cased_regression_finetuned_dcard

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

  • Loss: 0.6568
  • Mse: 0.6568
  • Mae: 0.5036
  • Rmse: 0.8104
  • Mape: inf
  • R Squared: 0.5925

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: 3e-05
  • train_batch_size: 16
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_steps: 891
  • num_epochs: 10

Training results

Training Loss Epoch Step Validation Loss Mse Mae Rmse Mape R Squared
1.0667 1.0 8917 0.9488 0.9488 0.6910 0.9741 inf 0.4113
0.8502 2.0 17834 0.7789 0.7789 0.6072 0.8825 inf 0.5167
0.6093 3.0 26751 0.7659 0.7659 0.5919 0.8751 inf 0.5248
0.5891 4.0 35668 0.7029 0.7029 0.5537 0.8384 inf 0.5639
0.5542 5.0 44585 0.6521 0.6521 0.5156 0.8075 inf 0.5954
0.5475 6.0 53502 0.6414 0.6414 0.5087 0.8009 inf 0.6020
0.4619 7.0 62419 0.6389 0.6389 0.5015 0.7993 inf 0.6036
0.4368 8.0 71336 0.6471 0.6471 0.5014 0.8044 inf 0.5985
0.4106 9.0 80253 0.6568 0.6568 0.5036 0.8104 inf 0.5925

Framework versions

  • Transformers 4.39.3
  • Pytorch 2.2.1
  • Datasets 2.18.0
  • Tokenizers 0.15.2