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sew-tiny-portuguese-cv

Automatic Speech Recognition
Transformers
PyTorch
Portuguese
sew
Generated from Trainer
hf-asr-leaderboard
robust-speech-event
Eval Results
Inference Endpoints
Model card Files Community
sew-tiny-portuguese-cv / README.md
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metadata
license: apache-2.0
tags:
  - generated_from_trainer
  - pt
  - robust-speech-event
datasets:
  - common_voice
model-index:
  - name: sew-tiny-portuguese-cv
    results: []

sew-tiny-portuguese-cv

This model is a fine-tuned version of lgris/sew-tiny-pt on the common_voice dataset. It achieves the following results on the evaluation set:

  • Loss: 0.5110
  • Wer: 0.2842

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: 0.0001
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 32
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 1000
  • training_steps: 40000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
No log 4.92 1000 0.8468 0.6494
3.4638 9.85 2000 0.4978 0.3815
3.4638 14.78 3000 0.4734 0.3417
0.9904 19.7 4000 0.4577 0.3344
0.9904 24.63 5000 0.4376 0.3170
0.8849 29.55 6000 0.4225 0.3118
0.8849 34.48 7000 0.4354 0.3080
0.819 39.41 8000 0.4434 0.3004
0.819 44.33 9000 0.4710 0.3132
0.7706 49.26 10000 0.4497 0.3064
0.7706 54.19 11000 0.4598 0.3100
0.7264 59.11 12000 0.4271 0.3013
0.7264 64.04 13000 0.4333 0.2959
0.6909 68.96 14000 0.4554 0.3019
0.6909 73.89 15000 0.4444 0.2888
0.6614 78.81 16000 0.4734 0.3081
0.6614 83.74 17000 0.4820 0.3058
0.6379 88.67 18000 0.4416 0.2950
0.6379 93.59 19000 0.4614 0.2974
0.6055 98.52 20000 0.4812 0.3018
0.6055 103.45 21000 0.4700 0.3018
0.5823 108.37 22000 0.4726 0.2999
0.5823 113.3 23000 0.4979 0.2887
0.5597 118.23 24000 0.4813 0.2980
0.5597 123.15 25000 0.4968 0.2972
0.542 128.08 26000 0.5331 0.3059
0.542 133.0 27000 0.5046 0.2978
0.5185 137.93 28000 0.4882 0.2922
0.5185 142.85 29000 0.4945 0.2938
0.499 147.78 30000 0.4971 0.2913
0.499 152.71 31000 0.4948 0.2873
0.4811 157.63 32000 0.4924 0.2918
0.4811 162.56 33000 0.5128 0.2911
0.4679 167.49 34000 0.5098 0.2892
0.4679 172.41 35000 0.4966 0.2863
0.456 177.34 36000 0.5033 0.2839
0.456 182.27 37000 0.5114 0.2875
0.4453 187.19 38000 0.5154 0.2859
0.4453 192.12 39000 0.5102 0.2847
0.4366 197.04 40000 0.5110 0.2842

Framework versions

  • Transformers 4.16.0.dev0
  • Pytorch 1.10.1+cu102
  • Datasets 1.17.1.dev0
  • Tokenizers 0.11.0