Hugging Face's logo

Abdallahsadek
/
speech-to-text-model2

Automatic Speech Recognition
Transformers
Safetensors
hubert
Generated from Trainer
Eval Results
Model card Files Community
speech-to-text-model2 / README.md
Abdallahsadek's picture
Abdallahsadek
Final model with Model Card
b97719a verified
preview code
|
raw
history blame contribute delete
3.08 kB
metadata
library_name: transformers
license: apache-2.0
base_model: facebook/hubert-large-ls960-ft
tags:
  - generated_from_trainer
datasets:
  - fleurs
metrics:
  - wer
model-index:
  - name: speech-to-text-model2
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: fleurs
          type: fleurs
          config: en_us
          split: None
          args: en_us
        metrics:
          - name: Wer
            type: wer
            value: 0.12054313689266581

speech-to-text-model2

This model is a fine-tuned version of facebook/hubert-large-ls960-ft on the fleurs dataset. It achieves the following results on the evaluation set:

  • Loss: 0.1971
  • Wer: 0.1205

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: 3e-05
  • train_batch_size: 2
  • eval_batch_size: 2
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 4
  • optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • num_epochs: 4
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.9469 0.1921 100 0.7808 0.1610
0.7241 0.3842 200 0.5663 0.1597
0.5805 0.5764 300 0.4338 0.1494
0.4717 0.7685 400 0.3221 0.1443
0.3769 0.9606 500 0.2380 0.1488
0.3659 1.1518 600 0.2276 0.1408
0.3316 1.3439 700 0.2139 0.1369
0.2798 1.5360 800 0.2151 0.1308
0.3207 1.7281 900 0.2075 0.1284
0.3199 1.9203 1000 0.2008 0.1265
0.2722 2.1114 1100 0.2009 0.1263
0.271 2.3036 1200 0.2077 0.1238
0.251 2.4957 1300 0.2121 0.1237
0.2918 2.6878 1400 0.1939 0.1224
0.2686 2.8799 1500 0.1992 0.1221
0.2668 3.0711 1600 0.1974 0.1226
0.2287 3.2632 1700 0.2060 0.1201
0.2546 3.4553 1800 0.1979 0.1200
0.2705 3.6475 1900 0.1938 0.1220
0.2647 3.8396 2000 0.1971 0.1205

Framework versions

  • Transformers 4.48.3
  • Pytorch 2.5.1+cu124
  • Datasets 3.3.2
  • Tokenizers 0.21.0