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sew-tiny-portuguese-cv8

Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Portuguese
sew
Generated from Trainer
hf-asr-leaderboard
robust-speech-event
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metadata
license: apache-2.0
tags:
  - generated_from_trainer
  - pt
  - robust-speech-event
datasets:
  - mozilla-foundation/common_voice_7_0
model-index:
  - name: sew-tiny-portuguese-cv8
    results: []

sew-tiny-portuguese-cv8

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: 0.4082
  • Wer: 0.3053

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 1.93 1000 2.9134 0.9767
2.9224 3.86 2000 2.8405 0.9789
2.9224 5.79 3000 2.8094 0.9800
2.8531 7.72 4000 2.7439 0.9891
2.8531 9.65 5000 2.7057 1.0159
2.7721 11.58 6000 2.7235 1.0709
2.7721 13.51 7000 2.5931 1.1035
2.6566 15.44 8000 2.2171 0.9884
2.6566 17.37 9000 1.2399 0.8081
1.9558 19.31 10000 0.9045 0.6353
1.9558 21.24 11000 0.7705 0.5533
1.4987 23.17 12000 0.7068 0.5165
1.4987 25.1 13000 0.6641 0.4718
1.3811 27.03 14000 0.6043 0.4470
1.3811 28.96 15000 0.5532 0.4268
1.2897 30.89 16000 0.5371 0.4101
1.2897 32.82 17000 0.5924 0.4150
1.225 34.75 18000 0.4949 0.3894
1.225 36.68 19000 0.5591 0.4045
1.193 38.61 20000 0.4927 0.3731
1.193 40.54 21000 0.4922 0.3712
1.1482 42.47 22000 0.4799 0.3662
1.1482 44.4 23000 0.4846 0.3648
1.1201 46.33 24000 0.4770 0.3623
1.1201 48.26 25000 0.4530 0.3426
1.0892 50.19 26000 0.4523 0.3527
1.0892 52.12 27000 0.4573 0.3443
1.0583 54.05 28000 0.4488 0.3353
1.0583 55.98 29000 0.4295 0.3285
1.0319 57.92 30000 0.4321 0.3220
1.0319 59.85 31000 0.4244 0.3236
1.0076 61.78 32000 0.4197 0.3201
1.0076 63.71 33000 0.4230 0.3208
0.9851 65.64 34000 0.4090 0.3127
0.9851 67.57 35000 0.4088 0.3133
0.9695 69.5 36000 0.4123 0.3088
0.9695 71.43 37000 0.4017 0.3090
0.9514 73.36 38000 0.4184 0.3086
0.9514 75.29 39000 0.4075 0.3043
0.944 77.22 40000 0.4082 0.3053

Framework versions

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