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metadata
library_name: transformers
license: mit
base_model: facebook/w2v-bert-2.0
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: muk-english-digits-classification
    results: []

muk-english-digits-classification

This model is a fine-tuned version of facebook/w2v-bert-2.0 on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.8012
  • Accuracy: 1.0

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: 2e-05
  • train_batch_size: 8
  • eval_batch_size: 1
  • seed: 42
  • optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 20

Training results

Training Loss Epoch Step Validation Loss Accuracy
2.3974 1.0 32 2.3805 0.1875
2.3542 2.0 64 2.3080 0.1875
2.2986 3.0 96 2.1997 0.3438
2.1947 4.0 128 2.0517 0.4062
2.0741 5.0 160 1.9182 0.4062
1.9479 6.0 192 1.8475 0.4688
1.8934 7.0 224 1.6724 0.5938
1.687 8.0 256 1.5422 0.6875
1.5745 9.0 288 1.3878 0.875
1.5288 10.0 320 1.2905 0.875
1.3518 11.0 352 1.1875 0.9375
1.2558 12.0 384 1.0936 0.9375
1.1538 13.0 416 1.0296 0.9688
1.186 14.0 448 0.9815 0.9688
1.033 15.0 480 0.9271 1.0
0.9828 16.0 512 0.8811 1.0
0.995 17.0 544 0.8454 0.9688
0.9213 18.0 576 0.8176 1.0
0.9313 19.0 608 0.8048 1.0
0.9029 20.0 640 0.8012 1.0

Framework versions

  • Transformers 4.57.2
  • Pytorch 2.9.0+cu126
  • Datasets 4.0.0
  • Tokenizers 0.22.1