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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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- pt |
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- robust-speech-event |
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datasets: |
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- common_voice |
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model-index: |
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- name: sew-tiny-portuguese-cv |
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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 6 |
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type: common_voice |
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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: 30.02 |
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- name: Test CER |
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type: cer |
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value: 10.34 |
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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: 56.46 |
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- name: Test CER |
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type: cer |
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value: 22.94 |
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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: 57.17 |
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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: 61.3 |
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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-cv |
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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: 0.5110 |
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- Wer: 0.2842 |
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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: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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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 | 4.92 | 1000 | 0.8468 | 0.6494 | |
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| 3.4638 | 9.85 | 2000 | 0.4978 | 0.3815 | |
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| 3.4638 | 14.78 | 3000 | 0.4734 | 0.3417 | |
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| 0.9904 | 19.7 | 4000 | 0.4577 | 0.3344 | |
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| 0.9904 | 24.63 | 5000 | 0.4376 | 0.3170 | |
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| 0.8849 | 29.55 | 6000 | 0.4225 | 0.3118 | |
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| 0.8849 | 34.48 | 7000 | 0.4354 | 0.3080 | |
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| 0.819 | 39.41 | 8000 | 0.4434 | 0.3004 | |
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| 0.819 | 44.33 | 9000 | 0.4710 | 0.3132 | |
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| 0.7706 | 49.26 | 10000 | 0.4497 | 0.3064 | |
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| 0.7706 | 54.19 | 11000 | 0.4598 | 0.3100 | |
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| 0.7264 | 59.11 | 12000 | 0.4271 | 0.3013 | |
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| 0.7264 | 64.04 | 13000 | 0.4333 | 0.2959 | |
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| 0.6909 | 68.96 | 14000 | 0.4554 | 0.3019 | |
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| 0.6909 | 73.89 | 15000 | 0.4444 | 0.2888 | |
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| 0.6614 | 78.81 | 16000 | 0.4734 | 0.3081 | |
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| 0.6614 | 83.74 | 17000 | 0.4820 | 0.3058 | |
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| 0.6379 | 88.67 | 18000 | 0.4416 | 0.2950 | |
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| 0.6379 | 93.59 | 19000 | 0.4614 | 0.2974 | |
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| 0.6055 | 98.52 | 20000 | 0.4812 | 0.3018 | |
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| 0.6055 | 103.45 | 21000 | 0.4700 | 0.3018 | |
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| 0.5823 | 108.37 | 22000 | 0.4726 | 0.2999 | |
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| 0.5823 | 113.3 | 23000 | 0.4979 | 0.2887 | |
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| 0.5597 | 118.23 | 24000 | 0.4813 | 0.2980 | |
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| 0.5597 | 123.15 | 25000 | 0.4968 | 0.2972 | |
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| 0.542 | 128.08 | 26000 | 0.5331 | 0.3059 | |
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| 0.542 | 133.0 | 27000 | 0.5046 | 0.2978 | |
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| 0.5185 | 137.93 | 28000 | 0.4882 | 0.2922 | |
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| 0.5185 | 142.85 | 29000 | 0.4945 | 0.2938 | |
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| 0.499 | 147.78 | 30000 | 0.4971 | 0.2913 | |
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| 0.499 | 152.71 | 31000 | 0.4948 | 0.2873 | |
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| 0.4811 | 157.63 | 32000 | 0.4924 | 0.2918 | |
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| 0.4811 | 162.56 | 33000 | 0.5128 | 0.2911 | |
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| 0.4679 | 167.49 | 34000 | 0.5098 | 0.2892 | |
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| 0.4679 | 172.41 | 35000 | 0.4966 | 0.2863 | |
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| 0.456 | 177.34 | 36000 | 0.5033 | 0.2839 | |
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| 0.456 | 182.27 | 37000 | 0.5114 | 0.2875 | |
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| 0.4453 | 187.19 | 38000 | 0.5154 | 0.2859 | |
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| 0.4453 | 192.12 | 39000 | 0.5102 | 0.2847 | |
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| 0.4366 | 197.04 | 40000 | 0.5110 | 0.2842 | |
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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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