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--- |
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language: |
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- hy |
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license: apache-2.0 |
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tags: |
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- automatic-speech-recognition |
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- mozilla-foundation/common_voice_8_0 |
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- generated_from_trainer |
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- robust-speech-event |
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- hy |
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- hf-asr-leaderboard |
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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: wav2vec2-xls-r-1b-hy-cv |
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results: |
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- task: |
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type: automatic-speech-recognition |
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name: Speech Recognition |
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dataset: |
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type: mozilla-foundation/common_voice_8_0 |
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name: Common Voice hy-AM |
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args: hy-AM |
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metrics: |
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- type: wer |
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value: 0.2755659640905542 |
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name: WER LM |
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- type: cer |
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value: 0.08659585230146687 |
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name: CER LM |
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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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# |
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This model is a fine-tuned version of [facebook/wav2vec2-xls-r-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - HY-AM dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: **0.4521** |
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- Wer: **0.5141** |
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- Cer: **0.1100** |
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- Wer+LM: **0.2756** |
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- Cer+LM: **0.0866** |
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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: 8e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 64 |
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- seed: 42 |
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- gradient_accumulation_steps: 8 |
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- total_train_batch_size: 128 |
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- optimizer: Adam with betas=(0.9,0.98) and epsilon=1e-08 |
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- lr_scheduler_type: tristage |
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- lr_scheduler_ratios: [0.1, 0.4, 0.5] |
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- training_steps: 1400 |
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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 | Cer | |
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|:-------------:|:------:|:----:|:---------------:|:------:|:------:| |
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| 6.1298 | 19.87 | 100 | 3.1204 | 1.0 | 1.0 | |
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| 2.7269 | 39.87 | 200 | 0.6200 | 0.7592 | 0.1755 | |
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| 1.4643 | 59.87 | 300 | 0.4796 | 0.5921 | 0.1277 | |
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| 1.1242 | 79.87 | 400 | 0.4637 | 0.5359 | 0.1145 | |
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| 0.9592 | 99.87 | 500 | 0.4521 | 0.5141 | 0.1100 | |
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| 0.8704 | 119.87 | 600 | 0.4736 | 0.4914 | 0.1045 | |
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| 0.7908 | 139.87 | 700 | 0.5394 | 0.5250 | 0.1124 | |
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| 0.7049 | 159.87 | 800 | 0.4822 | 0.4754 | 0.0985 | |
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| 0.6299 | 179.87 | 900 | 0.4890 | 0.4809 | 0.1028 | |
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| 0.5832 | 199.87 | 1000 | 0.5233 | 0.4813 | 0.1028 | |
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| 0.5145 | 219.87 | 1100 | 0.5350 | 0.4781 | 0.0994 | |
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| 0.4604 | 239.87 | 1200 | 0.5223 | 0.4715 | 0.0984 | |
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| 0.4226 | 259.87 | 1300 | 0.5167 | 0.4625 | 0.0953 | |
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| 0.3946 | 279.87 | 1400 | 0.5248 | 0.4614 | 0.0950 | |
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### Framework versions |
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- Transformers 4.17.0.dev0 |
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- Pytorch 1.10.2+cu102 |
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- Datasets 1.18.2.dev0 |
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- Tokenizers 0.11.0 |
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