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--- |
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language: |
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- te |
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license: apache-2.0 |
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tags: |
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- automatic-speech-recognition |
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- openslr_SLR66 |
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- generated_from_trainer |
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- robust-speech-event |
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- hf-asr-leaderboard |
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datasets: |
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- openslr |
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- SLR66 |
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metrics: |
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- wer |
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model-index: |
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- name: xls-r-1B-te |
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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: openslr |
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name: Open SLR |
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args: SLR66 |
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metrics: |
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- type: wer |
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value: 0.51 |
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name: Test WER |
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- type: cer |
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value: 0.097 |
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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-2b](https://huggingface.co/facebook/wav2vec2-xls-r-2b) on the OPENSLR_SLR66 - NA dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4253 |
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- Wer: 0.5109 |
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### Evaluation metrics |
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| Metric | Split | Decode with LM | Value | |
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|:------:|:------:|:--------------:|:---------:| |
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| WER | Train | No | | |
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| CER | Train | No | | |
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| WER | Test | No | | |
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| CER | Test | No | | |
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| WER | Train | Yes | | |
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| CER | Train | Yes | | |
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| WER | Test | Yes | | |
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| CER | Test | Yes | | |
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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: 2e-05 |
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- train_batch_size: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- gradient_accumulation_steps: 12 |
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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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- learning_rate: 3e-6 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 2000 |
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- num_epochs: 150.0 |
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- hidden_dropout: 0.15 |
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- mixed_precision_training: Native AMP |
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### Training results |
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### Framework versions |
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- Transformers 4.16.0.dev0 |
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- Pytorch 1.10.1+cu102 |
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- Datasets 1.17.1.dev0 |
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- Tokenizers 0.11.0 |
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