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akera
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whisper-medium-ach

Automatic Speech Recognition
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Safetensors
whisper
Generated from Trainer
Eval Results
Inference Endpoints
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whisper-medium-ach / README.md
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metadata
license: apache-2.0
tags:
  - generated_from_trainer
base_model: openai/whisper-medium
datasets:
  - generator
metrics:
  - wer
model-index:
  - name: whisper-medium-ach
    results:
      - task:
          type: automatic-speech-recognition
          name: Automatic Speech Recognition
        dataset:
          name: generator
          type: generator
          config: default
          split: train
          args: default
        metrics:
          - type: wer
            value: 62.298387096774185
            name: Wer

Visualize in Weights & Biases

whisper-medium-ach

This model is a fine-tuned version of openai/whisper-medium on the generator dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3501
  • Wer: 62.2984

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: 16
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • training_steps: 4000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
1.081 0.05 200 0.4844 138.8609
0.592 1.0248 400 0.3859 154.4355
0.5445 1.0748 600 0.3434 146.1694
0.3446 2.0495 800 0.3272 163.9113
0.2614 3.0242 1000 0.3098 86.2903
0.2542 3.0743 1200 0.3414 91.4315
0.1972 4.049 1400 0.3289 89.3145
0.1172 5.0237 1600 0.3224 100.1008
0.1226 5.0738 1800 0.3377 72.3286
0.0721 6.0485 2000 0.3277 105.8972
0.0504 7.0232 2200 0.3483 80.1411
0.0503 7.0732 2400 0.3514 95.0101
0.0375 8.048 2600 0.3378 64.5665
0.0348 9.0228 2800 0.3492 122.5806
0.0338 9.0727 3000 0.3502 88.6089
0.0273 10.0475 3200 0.3554 88.2560
0.0194 11.0222 3400 0.3501 62.2984
0.0165 11.0723 3600 0.3478 73.3871
0.0117 12.047 3800 0.3618 74.2440
0.0125 13.0218 4000 0.3587 97.6815

Framework versions

  • Transformers 4.41.0.dev0
  • Pytorch 2.2.0
  • Datasets 2.19.1.dev0
  • Tokenizers 0.19.1