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--- |
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language: |
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- gn |
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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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- gn |
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- robust-speech-event |
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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-300m-gn-cv8-3 |
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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 8.0 |
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type: mozilla-foundation/common_voice_8_0 |
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args: gn |
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metrics: |
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- name: Test WER |
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type: wer |
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value: 76.68 |
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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-xls-r-300m-gn-cv8-3 |
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This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the common_voice dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.9517 |
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- Wer: 0.8542 |
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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: 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: 5000 |
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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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| 19.9125 | 5.54 | 100 | 5.4279 | 1.0 | |
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| 3.8031 | 11.11 | 200 | 3.3070 | 1.0 | |
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| 3.3783 | 16.65 | 300 | 3.2450 | 1.0 | |
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| 3.3472 | 22.22 | 400 | 3.2424 | 1.0 | |
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| 3.2714 | 27.76 | 500 | 3.1100 | 1.0 | |
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| 3.2367 | 33.32 | 600 | 3.1091 | 1.0 | |
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| 3.1968 | 38.86 | 700 | 3.1013 | 1.0 | |
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| 3.2004 | 44.43 | 800 | 3.1173 | 1.0 | |
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| 3.1656 | 49.97 | 900 | 3.0682 | 1.0 | |
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| 3.1563 | 55.54 | 1000 | 3.0457 | 1.0 | |
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| 3.1356 | 61.11 | 1100 | 3.0139 | 1.0 | |
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| 3.086 | 66.65 | 1200 | 2.8108 | 1.0 | |
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| 2.954 | 72.22 | 1300 | 2.3238 | 1.0 | |
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| 2.6125 | 77.76 | 1400 | 1.6461 | 1.0 | |
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| 2.3296 | 83.32 | 1500 | 1.2834 | 0.9744 | |
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| 2.1345 | 88.86 | 1600 | 1.1091 | 0.9693 | |
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| 2.0346 | 94.43 | 1700 | 1.0273 | 0.9233 | |
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| 1.9611 | 99.97 | 1800 | 0.9642 | 0.9182 | |
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| 1.9066 | 105.54 | 1900 | 0.9590 | 0.9105 | |
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| 1.8178 | 111.11 | 2000 | 0.9679 | 0.9028 | |
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| 1.7799 | 116.65 | 2100 | 0.9007 | 0.8619 | |
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| 1.7726 | 122.22 | 2200 | 0.9689 | 0.8951 | |
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| 1.7389 | 127.76 | 2300 | 0.8876 | 0.8593 | |
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| 1.7151 | 133.32 | 2400 | 0.8716 | 0.8542 | |
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| 1.6842 | 138.86 | 2500 | 0.9536 | 0.8772 | |
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| 1.6449 | 144.43 | 2600 | 0.9296 | 0.8542 | |
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| 1.5978 | 149.97 | 2700 | 0.8895 | 0.8440 | |
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| 1.6515 | 155.54 | 2800 | 0.9162 | 0.8568 | |
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| 1.6586 | 161.11 | 2900 | 0.9039 | 0.8568 | |
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| 1.5966 | 166.65 | 3000 | 0.8627 | 0.8542 | |
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| 1.5695 | 172.22 | 3100 | 0.9549 | 0.8824 | |
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| 1.5699 | 177.76 | 3200 | 0.9332 | 0.8517 | |
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| 1.5297 | 183.32 | 3300 | 0.9163 | 0.8338 | |
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| 1.5367 | 188.86 | 3400 | 0.8822 | 0.8312 | |
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| 1.5586 | 194.43 | 3500 | 0.9217 | 0.8363 | |
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| 1.5429 | 199.97 | 3600 | 0.9564 | 0.8568 | |
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| 1.5273 | 205.54 | 3700 | 0.9508 | 0.8542 | |
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| 1.5043 | 211.11 | 3800 | 0.9374 | 0.8542 | |
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| 1.4724 | 216.65 | 3900 | 0.9622 | 0.8619 | |
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| 1.4794 | 222.22 | 4000 | 0.9550 | 0.8363 | |
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| 1.4843 | 227.76 | 4100 | 0.9577 | 0.8465 | |
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| 1.4781 | 233.32 | 4200 | 0.9543 | 0.8440 | |
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| 1.4507 | 238.86 | 4300 | 0.9553 | 0.8491 | |
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| 1.4997 | 244.43 | 4400 | 0.9728 | 0.8491 | |
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| 1.4371 | 249.97 | 4500 | 0.9543 | 0.8670 | |
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| 1.4825 | 255.54 | 4600 | 0.9636 | 0.8619 | |
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| 1.4187 | 261.11 | 4700 | 0.9609 | 0.8440 | |
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| 1.4363 | 266.65 | 4800 | 0.9567 | 0.8593 | |
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| 1.4463 | 272.22 | 4900 | 0.9581 | 0.8542 | |
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| 1.4117 | 277.76 | 5000 | 0.9517 | 0.8542 | |
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### Framework versions |
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- Transformers 4.16.0 |
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- Pytorch 1.10.0+cu111 |
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- Datasets 1.18.1 |
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- Tokenizers 0.11.0 |
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