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README.md
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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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- fleurs
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metrics:
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- wer
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model-index:
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- name: facebook/wav2vec2-xls-r-1b
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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: fleurs
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type: fleurs
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config: ps_af
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split: test
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args: ps_af
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metrics:
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- name: Wer
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type: wer
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value: 0.9322987721691678
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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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# facebook/wav2vec2-xls-r-1b
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This model is a fine-tuned version of [facebook/wav2vec2-xls-r-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on the fleurs dataset.
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It achieves the following results on the evaluation set:
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- Loss: 4.9040
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- Wer: 0.9323
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- Cer: 0.9546
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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: 8
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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: 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: 1000
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- training_steps: 500
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- mixed_precision_training: Native AMP
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### Training results
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| Training Loss | Epoch | Step | Cer | Validation Loss | Wer |
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|:-------------:|:-----:|:----:|:------:|:---------------:|:------:|
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| 19.9558 | 1.27 | 100 | 3.2660 | 20.9197 | 1.0 |
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| 19.7186 | 2.53 | 200 | 1.1692 | 19.2447 | 1.0 |
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| 15.203 | 3.8 | 300 | 15.0053| 0.9998 | 0.9687 |
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| 6.4303 | 5.06 | 400 | 6.5437 | 0.9632 | 0.9911 |
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| 4.5712 | 6.33 | 500 | 4.9040 | 0.9323 | 0.9546 |
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### Framework versions
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- Transformers 4.26.0.dev0
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- Pytorch 1.13.1+cu117
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- Datasets 2.7.1.dev0
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- Tokenizers 0.13.2
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