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wav2vec2-large-xls-r-1b-frisian-cv-8

Automatic Speech Recognition
Transformers
PyTorch
wav2vec2
Generated from Trainer
Eval Results
Inference Endpoints
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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_8_0
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+ metrics:
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+ - wer
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+ model-index:
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+ - name: wav2vec2-large-xls-r-1b-frisian-cv-8
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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: common_voice_8_0
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+ type: common_voice_8_0
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+ config: fy-NL
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+ split: validation
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+ args: fy-NL
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+ metrics:
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+ - name: Wer
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+ type: wer
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+ value: 0.15637051849735753
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+ ---
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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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+ # wav2vec2-large-xls-r-1b-frisian-cv-8
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+
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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 common_voice_8_0 dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.2219
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+ - Wer: 0.1564
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 7e-05
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+ - train_batch_size: 30
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+ - eval_batch_size: 8
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+ - seed: 42
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+ - optimizer: Adam with betas=(0.9,0.98) 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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+ - num_epochs: 50
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+ - mixed_precision_training: Native AMP
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Wer |
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+ |:-------------:|:-----:|:----:|:---------------:|:------:|
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+ | 4.9356 | 2.42 | 300 | 3.0022 | 1.0 |
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+ | 1.7278 | 4.84 | 600 | 0.4414 | 0.4147 |
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+ | 0.9407 | 7.26 | 900 | 0.3058 | 0.2955 |
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+ | 0.943 | 9.68 | 1200 | 0.2678 | 0.2530 |
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+ | 0.7468 | 12.1 | 1500 | 0.2443 | 0.2237 |
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+ | 0.6009 | 14.52 | 1800 | 0.2381 | 0.2097 |
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+ | 0.6101 | 16.94 | 2100 | 0.2339 | 0.2003 |
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+ | 0.5646 | 19.35 | 2400 | 0.2357 | 0.2047 |
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+ | 0.5875 | 21.77 | 2700 | 0.2219 | 0.1914 |
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+ | 0.5245 | 24.19 | 3000 | 0.2525 | 0.1807 |
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+ | 0.5971 | 26.61 | 3300 | 0.2432 | 0.1784 |
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+ | 0.563 | 29.03 | 3600 | 0.2454 | 0.1753 |
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+ | 0.4441 | 31.45 | 3900 | 0.2237 | 0.1776 |
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+ | 0.5552 | 33.87 | 4200 | 0.2313 | 0.1629 |
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+ | 0.5568 | 36.29 | 4500 | 0.2318 | 0.1602 |
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+ | 0.4342 | 38.71 | 4800 | 0.2324 | 0.1556 |
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+ | 0.4723 | 41.13 | 5100 | 0.2296 | 0.1602 |
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+ | 0.3357 | 43.55 | 5400 | 0.2267 | 0.1575 |
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+ | 0.4588 | 45.97 | 5700 | 0.2243 | 0.1558 |
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+ | 0.4594 | 48.39 | 6000 | 0.2219 | 0.1564 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.28.1
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+ - Pytorch 2.0.0+cu117
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+ - Datasets 2.11.0
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+ - Tokenizers 0.13.3