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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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- automatic-speech-recognition |
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- generated_from_trainer |
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- hf-asr-leaderboard |
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- mozilla-foundation/common_voice_7_0 |
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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: wav2vec2_base_10k_8khz_pt_cv7_2 |
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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: 36.9 |
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- name: Test CER |
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type: cer |
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value: 14.82 |
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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: 40.53 |
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- name: Test CER |
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type: cer |
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value: 16.95 |
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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: 37.15 |
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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: 38.95 |
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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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# wav2vec2_base_10k_8khz_pt_cv7_2 |
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This model is a fine-tuned version of [lgris/seasr_2022_base_10k_8khz_pt](https://huggingface.co/lgris/seasr_2022_base_10k_8khz_pt) on the common_voice dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 76.3426 |
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- Wer: 0.1979 |
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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: 1e-05 |
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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: 2 |
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- total_train_batch_size: 16 |
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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: 100 |
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- training_steps: 10000 |
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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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| 189.1362 | 0.65 | 500 | 80.6347 | 0.2139 | |
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| 174.2587 | 1.3 | 1000 | 80.2062 | 0.2116 | |
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| 164.676 | 1.95 | 1500 | 78.2161 | 0.2073 | |
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| 176.5856 | 2.6 | 2000 | 78.8920 | 0.2074 | |
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| 164.3583 | 3.25 | 2500 | 77.2865 | 0.2066 | |
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| 161.414 | 3.9 | 3000 | 77.8888 | 0.2048 | |
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| 158.283 | 4.55 | 3500 | 77.3472 | 0.2033 | |
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| 159.2265 | 5.19 | 4000 | 79.0953 | 0.2036 | |
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| 156.3967 | 5.84 | 4500 | 76.6855 | 0.2029 | |
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| 154.2743 | 6.49 | 5000 | 77.7785 | 0.2015 | |
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| 156.6497 | 7.14 | 5500 | 77.1220 | 0.2033 | |
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| 157.3038 | 7.79 | 6000 | 76.2926 | 0.2027 | |
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| 162.8151 | 8.44 | 6500 | 76.7602 | 0.2013 | |
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| 151.8613 | 9.09 | 7000 | 77.4777 | 0.2011 | |
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| 153.0225 | 9.74 | 7500 | 76.5206 | 0.2001 | |
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| 157.52 | 10.39 | 8000 | 76.1061 | 0.2006 | |
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| 145.0592 | 11.04 | 8500 | 76.7855 | 0.1992 | |
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| 150.0066 | 11.69 | 9000 | 76.0058 | 0.1988 | |
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| 146.8128 | 12.34 | 9500 | 76.2853 | 0.1987 | |
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| 146.9148 | 12.99 | 10000 | 76.3426 | 0.1979 | |
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### Framework versions |
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- Transformers 4.16.2 |
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- Pytorch 1.10.0+cu111 |
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- Datasets 1.18.3 |
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- Tokenizers 0.11.0 |
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