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End of training
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metadata
license: apache-2.0
base_model: honzapucalek/hc-czech-large-v3-v2-independent
tags:
  - generated_from_trainer
datasets:
  - honzapucalek/impaired_v3_independent_all
metrics:
  - wer
model-index:
  - name: impaired-v3-independent-all-hc-train
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: honzapucalek/impaired_v3_independent_all cs
          type: honzapucalek/impaired_v3_independent_all
          config: cs
          split: test
          args: cs
        metrics:
          - name: Wer
            type: wer
            value: 0.4058704453441296

impaired-v3-independent-all-hc-train

This model is a fine-tuned version of honzapucalek/hc-czech-large-v3-v2-independent on the honzapucalek/impaired_v3_independent_all cs dataset. It achieves the following results on the evaluation set:

  • Loss: 1.4176
  • Wer: 0.4059

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: 1e-05
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 16
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • training_steps: 5000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.006 13.99 1000 1.1860 0.4332
0.0022 27.97 2000 1.1733 0.4211
0.0001 41.96 3000 1.3533 0.4109
0.0 55.94 4000 1.4029 0.4099
0.0 69.93 5000 1.4176 0.4059

Framework versions

  • Transformers 4.37.2
  • Pytorch 2.1.2+cu121
  • Datasets 2.16.1
  • Tokenizers 0.15.1