Hugging Face's logo

miosipof
/
asr_Synth_EasyCall_v0.1

PEFT
Safetensors
Italian
Generated from Trainer
Eval Results
Model card Files Community
asr_Synth_EasyCall_v0.1 / README.md
miosipof's picture
miosipof
End of training
abbd403 verified
preview code
|
raw
history blame contribute delete
3.25 kB
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: 66.77419354838709
            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: 0.9709
  • Wer: 66.7742

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: 15
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
6.1405 0.6897 50 5.7981 205.1613
4.968 1.3793 100 5.3200 164.8387
4.2444 2.0690 150 4.7663 85.8065
3.6175 2.7586 200 4.0413 83.8710
3.0351 3.4483 250 3.6257 80.3226
2.668 4.1379 300 3.2450 75.8065
2.3178 4.8276 350 2.8196 75.1613
1.9613 5.5172 400 2.3047 73.8710
1.5398 6.2069 450 1.8564 73.8710
1.2771 6.8966 500 1.5804 76.4516
1.0752 7.5862 550 1.3762 75.1613
0.8899 8.2759 600 1.2049 77.0968
0.7684 8.9655 650 1.1252 75.1613
0.7242 9.6552 700 1.0776 74.1935
0.67 10.3448 750 1.0567 72.9032
0.6405 11.0345 800 1.0334 73.2258
0.622 11.7241 850 1.0179 74.1935
0.5874 12.4138 900 1.0067 71.2903
0.5601 13.1034 950 0.9863 67.0968
0.544 13.7931 1000 0.9855 67.0968
0.538 14.4828 1050 0.9709 66.7742

Framework versions

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