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--- |
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language: |
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- pt |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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- hf-asr-leaderboard |
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- pt |
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- robust-speech-event |
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datasets: |
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- mozilla-foundation/common_voice_7_0 |
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model-index: |
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- name: sew-tiny-portuguese-cv7 |
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results: |
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- task: |
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name: Automatic Speech Recognition |
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type: automatic-speech-recognition |
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dataset: |
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name: Common Voice 7 |
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type: mozilla-foundation/common_voice_7_0 |
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args: pt |
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metrics: |
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- name: Test WER |
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type: wer |
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value: 28.9 |
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- name: Test CER |
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type: cer |
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value: 9.41 |
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- task: |
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name: Automatic Speech Recognition |
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type: automatic-speech-recognition |
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dataset: |
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name: Robust Speech Event - Dev Data |
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type: speech-recognition-community-v2/dev_data |
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args: sv |
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metrics: |
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- name: Test WER |
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type: wer |
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value: 47.27 |
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- name: Test CER |
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type: cer |
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value: 19.62 |
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- task: |
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name: Automatic Speech Recognition |
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type: automatic-speech-recognition |
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dataset: |
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name: Robust Speech Event - Dev Data |
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type: speech-recognition-community-v2/dev_data |
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args: pt |
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metrics: |
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- name: Test WER |
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type: wer |
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value: 47.3 |
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- task: |
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name: Automatic Speech Recognition |
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type: automatic-speech-recognition |
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dataset: |
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name: Robust Speech Event - Test Data |
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type: speech-recognition-community-v2/eval_data |
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args: pt |
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metrics: |
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- name: Test WER |
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type: wer |
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value: 49.83 |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# sew-tiny-portuguese-cv7 |
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This model is a fine-tuned version of [lgris/sew-tiny-pt](https://huggingface.co/lgris/sew-tiny-pt) on the common_voice dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4232 |
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- Wer: 0.2745 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.0001 |
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- train_batch_size: 16 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 32 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 1000 |
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- training_steps: 40000 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Wer | |
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|:-------------:|:------:|:-----:|:---------------:|:------:| |
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| No log | 2.6 | 1000 | 1.0034 | 0.7308 | |
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| 4.1307 | 5.19 | 2000 | 0.6274 | 0.4721 | |
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| 4.1307 | 7.79 | 3000 | 0.5541 | 0.4130 | |
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| 1.3117 | 10.39 | 4000 | 0.5302 | 0.3880 | |
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| 1.3117 | 12.99 | 5000 | 0.5082 | 0.3644 | |
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| 1.2047 | 15.58 | 6000 | 0.4818 | 0.3539 | |
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| 1.2047 | 18.18 | 7000 | 0.4822 | 0.3477 | |
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| 1.14 | 20.78 | 8000 | 0.4781 | 0.3428 | |
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| 1.14 | 23.38 | 9000 | 0.4840 | 0.3401 | |
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| 1.0818 | 25.97 | 10000 | 0.4613 | 0.3251 | |
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| 1.0818 | 28.57 | 11000 | 0.4569 | 0.3257 | |
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| 1.0451 | 31.17 | 12000 | 0.4494 | 0.3132 | |
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| 1.0451 | 33.77 | 13000 | 0.4560 | 0.3201 | |
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| 1.011 | 36.36 | 14000 | 0.4687 | 0.3174 | |
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| 1.011 | 38.96 | 15000 | 0.4397 | 0.3122 | |
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| 0.9785 | 41.56 | 16000 | 0.4605 | 0.3173 | |
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| 0.9785 | 44.16 | 17000 | 0.4380 | 0.3064 | |
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| 0.9458 | 46.75 | 18000 | 0.4372 | 0.3048 | |
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| 0.9458 | 49.35 | 19000 | 0.4426 | 0.3039 | |
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| 0.9126 | 51.95 | 20000 | 0.4317 | 0.2962 | |
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| 0.9126 | 54.54 | 21000 | 0.4345 | 0.2960 | |
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| 0.8926 | 57.14 | 22000 | 0.4365 | 0.2948 | |
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| 0.8926 | 59.74 | 23000 | 0.4306 | 0.2940 | |
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| 0.8654 | 62.34 | 24000 | 0.4303 | 0.2928 | |
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| 0.8654 | 64.93 | 25000 | 0.4351 | 0.2915 | |
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| 0.8373 | 67.53 | 26000 | 0.4340 | 0.2909 | |
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| 0.8373 | 70.13 | 27000 | 0.4279 | 0.2907 | |
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| 0.83 | 72.73 | 28000 | 0.4214 | 0.2867 | |
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| 0.83 | 75.32 | 29000 | 0.4256 | 0.2849 | |
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| 0.8062 | 77.92 | 30000 | 0.4281 | 0.2826 | |
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| 0.8062 | 80.52 | 31000 | 0.4398 | 0.2865 | |
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| 0.7846 | 83.12 | 32000 | 0.4218 | 0.2812 | |
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| 0.7846 | 85.71 | 33000 | 0.4227 | 0.2791 | |
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| 0.7697 | 88.31 | 34000 | 0.4200 | 0.2767 | |
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| 0.7697 | 90.91 | 35000 | 0.4285 | 0.2791 | |
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| 0.7539 | 93.51 | 36000 | 0.4238 | 0.2777 | |
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| 0.7539 | 96.1 | 37000 | 0.4288 | 0.2757 | |
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| 0.7413 | 98.7 | 38000 | 0.4205 | 0.2748 | |
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| 0.7413 | 101.3 | 39000 | 0.4241 | 0.2761 | |
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| 0.7348 | 103.89 | 40000 | 0.4232 | 0.2745 | |
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### Framework versions |
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- Transformers 4.16.0.dev0 |
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- Pytorch 1.10.1+cu102 |
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- Datasets 1.17.1.dev0 |
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- Tokenizers 0.11.0 |
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