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update model card README.md
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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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- common_voice
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model-index:
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- name: wav2vec2-large-xls-r-300m-or-d5
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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-or-d5
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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: 0.9571
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- Wer: 0.5450
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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: 0.000111
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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: 800
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- num_epochs: 200
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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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| 9.2958 | 12.5 | 300 | 4.9014 | 1.0 |
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| 3.4065 | 25.0 | 600 | 3.5150 | 1.0 |
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| 1.5402 | 37.5 | 900 | 0.8356 | 0.7249 |
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| 0.6049 | 50.0 | 1200 | 0.7754 | 0.6349 |
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| 0.4074 | 62.5 | 1500 | 0.7994 | 0.6217 |
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| 0.3097 | 75.0 | 1800 | 0.8815 | 0.5985 |
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| 0.2593 | 87.5 | 2100 | 0.8532 | 0.5754 |
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| 0.2097 | 100.0 | 2400 | 0.9077 | 0.5648 |
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| 0.1784 | 112.5 | 2700 | 0.9047 | 0.5668 |
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| 0.1567 | 125.0 | 3000 | 0.9019 | 0.5728 |
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| 0.1315 | 137.5 | 3300 | 0.9295 | 0.5827 |
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| 0.1125 | 150.0 | 3600 | 0.9256 | 0.5681 |
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| 0.1035 | 162.5 | 3900 | 0.9148 | 0.5496 |
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| 0.0901 | 175.0 | 4200 | 0.9480 | 0.5483 |
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| 0.0817 | 187.5 | 4500 | 0.9799 | 0.5516 |
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| 0.079 | 200.0 | 4800 | 0.9571 | 0.5450 |
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### Framework versions
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- Transformers 4.16.2
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- Pytorch 1.10.0+cu111
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- Datasets 1.18.3
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- Tokenizers 0.11.0
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