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deberta-v3-xsmall-cotat-recommened-hp

This model is a fine-tuned version of microsoft/deberta-v3-xsmall on the DandinPower/review_cleanonlytitleandtext dataset. It achieves the following results on the evaluation set:

  • Loss: 0.8783
  • Accuracy: 0.6263
  • Macro F1: 0.6285

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: 4.5e-05
  • train_batch_size: 16
  • eval_batch_size: 16
  • seed: 42
  • gradient_accumulation_steps: 8
  • total_train_batch_size: 128
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 1000
  • num_epochs: 3

Training results

Training Loss Epoch Step Validation Loss Accuracy Macro F1
1.61 0.4571 100 1.6076 0.22 0.1631
1.5063 0.9143 200 1.2854 0.4094 0.2942
1.2016 1.3714 300 1.0481 0.5529 0.5311
1.0219 1.8286 400 0.9338 0.6093 0.6020
0.9362 2.2857 500 0.8919 0.6261 0.6239
0.9097 2.7429 600 0.8783 0.6263 0.6285

Framework versions

  • Transformers 4.40.2
  • Pytorch 2.3.0+cu121
  • Datasets 2.19.1
  • Tokenizers 0.19.1
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Dataset used to train DandinPower/deberta-v3-xsmall-cotat-recommened-hp

Evaluation results

  • Accuracy on DandinPower/review_cleanonlytitleandtext
    self-reported
    0.626