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asr_Synth_EasyCall_v0.2

PEFT
Safetensors
Italian
Generated from Trainer
Eval Results
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asr_Synth_EasyCall_v0.2 / README.md
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metadata
library_name: peft
language:
  - it
license: apache-2.0
base_model: openai/whisper-medium
tags:
  - generated_from_trainer
datasets:
  - Dysarthria_Synthetic_Easycall_Common
metrics:
  - wer
model-index:
  - name: Whisper Medium
    results:
      - task:
          type: automatic-speech-recognition
          name: Automatic Speech Recognition
        dataset:
          name: Dysarthria_Synthetic_Easycall_Common
          type: Dysarthria_Synthetic_Easycall_Common
          config: default
          split: train
          args: default
        metrics:
          - type: wer
            value: 70.3225806451613
            name: Wer

Whisper Medium

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

  • Loss: 0.9647
  • Wer: 70.3226

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: 16
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 32
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: reduce_lr_on_plateau
  • lr_scheduler_warmup_steps: 100
  • num_epochs: 30
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
6.0651 0.6897 50 5.7375 162.9032
4.9066 1.3793 100 5.3309 93.5484
4.2186 2.0690 150 4.7377 89.3548
3.628 2.7586 200 4.0118 81.6129
3.0181 3.4483 250 3.6058 81.6129
2.6682 4.1379 300 3.2728 78.3871
2.3183 4.8276 350 2.8405 75.4839
1.9084 5.5172 400 2.1841 71.9355
1.2191 6.2069 450 1.2534 73.5484
0.8483 6.8966 500 1.1853 73.5484
0.8115 7.5862 550 1.1503 70.9677
0.7512 8.2759 600 1.1072 73.5484
0.7064 8.9655 650 1.0806 74.5161
0.6779 9.6552 700 1.0477 75.1613
0.6345 10.3448 750 1.0352 74.8387
0.6097 11.0345 800 1.0186 73.8710
0.5927 11.7241 850 1.0120 74.5161
0.5619 12.4138 900 1.0017 73.5484
0.5349 13.1034 950 0.9879 70.0
0.5207 13.7931 1000 0.9900 70.0
0.5168 14.4828 1050 0.9828 173.8710
0.4703 15.1724 1100 0.9676 73.5484
0.476 15.8621 1150 0.9729 175.8065
0.4443 16.5517 1200 0.9652 74.1935
0.4215 17.2414 1250 0.9635 176.1290
0.4206 17.9310 1300 0.9631 179.3548
0.3971 18.6207 1350 0.9687 70.6452
0.3838 19.3103 1400 0.9543 147.7419
0.3791 20.0 1450 0.9594 68.3871
0.3441 20.6897 1500 0.9608 257.0968
0.3574 21.3793 1550 0.9589 71.2903
0.3323 22.0690 1600 0.9619 69.6774
0.3187 22.7586 1650 0.9552 154.1935
0.3011 23.4483 1700 0.9568 67.0968
0.2997 24.1379 1750 0.9580 70.9677
0.287 24.8276 1800 0.9566 70.6452
0.2747 25.5172 1850 0.9694 68.3871
0.2665 26.2069 1900 0.9544 69.0323
0.2565 26.8966 1950 0.9518 155.8065
0.2448 27.5862 2000 0.9579 68.7097
0.2377 28.2759 2050 0.9589 67.0968
0.2323 28.9655 2100 0.9590 68.7097
0.2224 29.6552 2150 0.9647 70.3226

Framework versions

  • PEFT 0.14.0
  • Transformers 4.45.2
  • Pytorch 2.2.0
  • Datasets 3.2.0
  • Tokenizers 0.20.3