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--- |
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language: |
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- ur |
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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_9_0 |
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- generated_from_trainer |
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datasets: |
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- mozilla-foundation/common_voice_9_0 |
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metrics: |
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- wer |
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base_model: facebook/wav2vec2-xls-r-300m |
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model-index: |
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- name: XLS-R-300M - Urdu |
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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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name: Common Voice 9 |
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type: mozilla-foundation/common_voice_9_0 |
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args: ur |
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metrics: |
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- type: wer |
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value: 23.75 |
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name: Test WER |
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- type: cer |
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value: 8.31 |
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name: Test CER |
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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-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the MOZILLA-FOUNDATION/COMMON_VOICE_9_0 - UR dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4147 |
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- Wer: 0.3172 |
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- Cer: 0.1050 |
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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: 7.5e-05 |
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- train_batch_size: 64 |
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- eval_batch_size: 64 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 128 |
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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_ratio: 0.1 |
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- training_steps: 5108 |
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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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| 3.2894 | 7.83 | 400 | 3.1501 | 1.0 | 1.0 | |
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| 1.8586 | 15.68 | 800 | 0.8871 | 0.6721 | 0.2402 | |
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| 1.3431 | 23.52 | 1200 | 0.5813 | 0.5502 | 0.1939 | |
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| 1.2052 | 31.37 | 1600 | 0.4956 | 0.4788 | 0.1665 | |
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| 1.1097 | 39.21 | 2000 | 0.4447 | 0.4143 | 0.1397 | |
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| 1.0528 | 47.06 | 2400 | 0.4439 | 0.3961 | 0.1333 | |
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| 0.9939 | 54.89 | 2800 | 0.4348 | 0.4014 | 0.1379 | |
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| 0.9441 | 62.74 | 3200 | 0.4236 | 0.3653 | 0.1223 | |
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| 0.913 | 70.58 | 3600 | 0.4309 | 0.3475 | 0.1157 | |
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| 0.8678 | 78.43 | 4000 | 0.4270 | 0.3337 | 0.1110 | |
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| 0.8414 | 86.27 | 4400 | 0.4158 | 0.3220 | 0.1070 | |
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| 0.817 | 94.12 | 4800 | 0.4185 | 0.3231 | 0.1072 | |
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### Framework versions |
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- Transformers 4.19.0.dev0 |
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- Pytorch 1.11.0+cu102 |
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- Datasets 2.1.1.dev0 |
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- Tokenizers 0.12.1 |
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