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--- |
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license: apache-2.0 |
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language: tt |
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tags: |
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- automatic-speech-recognition |
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- common_voice |
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- generated_from_trainer |
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- hf-asr-leaderboard |
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- robust-speech-event |
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- tt |
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datasets: |
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- common_voice |
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model-index: |
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- name: wav2vec2-large-xlsr-53-W2V2-TATAR-SMALL |
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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: tt |
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metrics: |
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- name: Test WER |
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type: wer |
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value: 53.16 |
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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-large-xlsr-53-W2V2-TATAR-SMALL |
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This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the common_voice dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4714 |
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- Wer: 0.5316 |
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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: 0.0003 |
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- train_batch_size: 16 |
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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: 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: 500 |
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- num_epochs: 30 |
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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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| 6.2446 | 1.17 | 400 | 3.2621 | 1.0 | |
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| 1.739 | 2.35 | 800 | 0.5832 | 0.7688 | |
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| 0.4718 | 3.52 | 1200 | 0.4785 | 0.6824 | |
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| 0.3574 | 4.69 | 1600 | 0.4814 | 0.6792 | |
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| 0.2946 | 5.86 | 2000 | 0.4484 | 0.6506 | |
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| 0.2674 | 7.04 | 2400 | 0.4612 | 0.6225 | |
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| 0.2349 | 8.21 | 2800 | 0.4600 | 0.6050 | |
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| 0.2206 | 9.38 | 3200 | 0.4772 | 0.6048 | |
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| 0.2072 | 10.56 | 3600 | 0.4676 | 0.6106 | |
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| 0.1984 | 11.73 | 4000 | 0.4816 | 0.6079 | |
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| 0.1793 | 12.9 | 4400 | 0.4616 | 0.5836 | |
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| 0.172 | 14.08 | 4800 | 0.4808 | 0.5860 | |
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| 0.1624 | 15.25 | 5200 | 0.4854 | 0.5820 | |
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| 0.156 | 16.42 | 5600 | 0.4609 | 0.5656 | |
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| 0.1448 | 17.59 | 6000 | 0.4926 | 0.5817 | |
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| 0.1406 | 18.77 | 6400 | 0.4638 | 0.5654 | |
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| 0.1337 | 19.94 | 6800 | 0.4731 | 0.5652 | |
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| 0.1317 | 21.11 | 7200 | 0.4861 | 0.5639 | |
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| 0.1179 | 22.29 | 7600 | 0.4766 | 0.5521 | |
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| 0.1197 | 23.46 | 8000 | 0.4824 | 0.5584 | |
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| 0.1096 | 24.63 | 8400 | 0.5006 | 0.5559 | |
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| 0.1038 | 25.81 | 8800 | 0.4994 | 0.5440 | |
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| 0.0992 | 26.98 | 9200 | 0.4867 | 0.5405 | |
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| 0.0984 | 28.15 | 9600 | 0.4798 | 0.5361 | |
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| 0.0943 | 29.33 | 10000 | 0.4714 | 0.5316 | |
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### Framework versions |
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- Transformers 4.11.3 |
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- Pytorch 1.10.0+cu111 |
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- Datasets 1.14.0 |
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- Tokenizers 0.10.3 |
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