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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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- mozilla-foundation/common_voice_8_0 |
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model-index: |
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- name: sew-tiny-portuguese-cv8 |
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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 8 |
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type: mozilla-foundation/common_voice_8_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: 33.71 |
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- name: Test CER |
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type: cer |
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value: 10.69 |
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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: 52.79 |
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- name: Test CER |
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type: cer |
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value: 20.98 |
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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: 53.18 |
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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: 55.23 |
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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-cv8 |
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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: 0.4082 |
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- Wer: 0.3053 |
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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 | 1.93 | 1000 | 2.9134 | 0.9767 | |
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| 2.9224 | 3.86 | 2000 | 2.8405 | 0.9789 | |
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| 2.9224 | 5.79 | 3000 | 2.8094 | 0.9800 | |
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| 2.8531 | 7.72 | 4000 | 2.7439 | 0.9891 | |
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| 2.8531 | 9.65 | 5000 | 2.7057 | 1.0159 | |
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| 2.7721 | 11.58 | 6000 | 2.7235 | 1.0709 | |
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| 2.7721 | 13.51 | 7000 | 2.5931 | 1.1035 | |
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| 2.6566 | 15.44 | 8000 | 2.2171 | 0.9884 | |
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| 2.6566 | 17.37 | 9000 | 1.2399 | 0.8081 | |
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| 1.9558 | 19.31 | 10000 | 0.9045 | 0.6353 | |
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| 1.9558 | 21.24 | 11000 | 0.7705 | 0.5533 | |
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| 1.4987 | 23.17 | 12000 | 0.7068 | 0.5165 | |
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| 1.4987 | 25.1 | 13000 | 0.6641 | 0.4718 | |
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| 1.3811 | 27.03 | 14000 | 0.6043 | 0.4470 | |
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| 1.3811 | 28.96 | 15000 | 0.5532 | 0.4268 | |
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| 1.2897 | 30.89 | 16000 | 0.5371 | 0.4101 | |
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| 1.2897 | 32.82 | 17000 | 0.5924 | 0.4150 | |
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| 1.225 | 34.75 | 18000 | 0.4949 | 0.3894 | |
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| 1.225 | 36.68 | 19000 | 0.5591 | 0.4045 | |
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| 1.193 | 38.61 | 20000 | 0.4927 | 0.3731 | |
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| 1.193 | 40.54 | 21000 | 0.4922 | 0.3712 | |
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| 1.1482 | 42.47 | 22000 | 0.4799 | 0.3662 | |
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| 1.1482 | 44.4 | 23000 | 0.4846 | 0.3648 | |
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| 1.1201 | 46.33 | 24000 | 0.4770 | 0.3623 | |
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| 1.1201 | 48.26 | 25000 | 0.4530 | 0.3426 | |
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| 1.0892 | 50.19 | 26000 | 0.4523 | 0.3527 | |
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| 1.0892 | 52.12 | 27000 | 0.4573 | 0.3443 | |
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| 1.0583 | 54.05 | 28000 | 0.4488 | 0.3353 | |
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| 1.0583 | 55.98 | 29000 | 0.4295 | 0.3285 | |
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| 1.0319 | 57.92 | 30000 | 0.4321 | 0.3220 | |
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| 1.0319 | 59.85 | 31000 | 0.4244 | 0.3236 | |
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| 1.0076 | 61.78 | 32000 | 0.4197 | 0.3201 | |
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| 1.0076 | 63.71 | 33000 | 0.4230 | 0.3208 | |
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| 0.9851 | 65.64 | 34000 | 0.4090 | 0.3127 | |
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| 0.9851 | 67.57 | 35000 | 0.4088 | 0.3133 | |
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| 0.9695 | 69.5 | 36000 | 0.4123 | 0.3088 | |
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| 0.9695 | 71.43 | 37000 | 0.4017 | 0.3090 | |
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| 0.9514 | 73.36 | 38000 | 0.4184 | 0.3086 | |
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| 0.9514 | 75.29 | 39000 | 0.4075 | 0.3043 | |
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| 0.944 | 77.22 | 40000 | 0.4082 | 0.3053 | |
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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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