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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- common_voice |
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model-index: |
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- name: wav2vec2-large-xls-r-300m-Urdu |
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results: [] |
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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-xls-r-300m-Urdu |
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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: 1.5867 |
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- Wer: 0.6240 |
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- Cer: 0.2579 |
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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: 4 |
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- total_train_batch_size: 64 |
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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: 200 |
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- num_epochs: 100 |
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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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| 11.1231 | 8.31 | 100 | 3.5275 | 1.0 | 1.0 | |
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| 3.4028 | 16.63 | 200 | 3.1164 | 1.0 | 1.0 | |
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| 3.1973 | 24.94 | 300 | 2.5590 | 1.0 | 1.0 | |
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| 1.3774 | 33.31 | 400 | 1.4729 | 0.7646 | 0.3325 | |
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| 0.5427 | 41.63 | 500 | 1.4140 | 0.6939 | 0.3001 | |
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| 0.3541 | 49.94 | 600 | 1.4532 | 0.6580 | 0.2815 | |
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| 0.26 | 58.31 | 700 | 1.5309 | 0.6403 | 0.2726 | |
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| 0.2025 | 66.63 | 800 | 1.5230 | 0.6310 | 0.2655 | |
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| 0.171 | 74.94 | 900 | 1.5578 | 0.6336 | 0.2632 | |
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| 0.1511 | 83.31 | 1000 | 1.5733 | 0.6321 | 0.2635 | |
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| 0.1352 | 91.63 | 1100 | 1.6022 | 0.6255 | 0.2608 | |
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| 0.1192 | 99.94 | 1200 | 1.5867 | 0.6240 | 0.2579 | |
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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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