metadata

license: apache-2.0
base_model: honzapucalek/p6_commonvoice_16_1
tags:
  - generated_from_trainer
datasets:
  - honzapucalek/p6_mild
metrics:
  - wer
model-index:
  - name: p6_commonvoice_mild
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: honzapucalek/p6_mild cs
          type: honzapucalek/p6_mild
          config: cs
          split: test
          args: cs
        metrics:
          - name: Wer
            type: wer
            value: 0.15919112057168922

p6_commonvoice_mild

This model is a fine-tuned version of honzapucalek/p6_commonvoice_16_1 on the honzapucalek/p6_mild cs dataset. It achieves the following results on the evaluation set:

Loss: 0.6098
Wer: 0.1592

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
0.0001	46.51	1000	0.5156	0.1606
0.0	93.02	2000	0.5644	0.1584
0.0	139.53	3000	0.5888	0.1577
0.0	186.05	4000	0.6044	0.1592
0.0	232.56	5000	0.6098	0.1592

Framework versions

Transformers 4.37.2
Pytorch 2.1.2+cu121
Datasets 2.16.1
Tokenizers 0.15.1