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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_13_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 |
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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_13_0 |
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type: common_voice_13_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: 0.1492598825428444 |
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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: test |
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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: 0.15356265356265356 |
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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_13_0 |
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type: common_voice_13_0 |
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config: fy-NL |
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split: test |
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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: 0.14712316399874995 |
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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-1b-frisian |
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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_13_0 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2204 |
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- Wer: 0.1493 |
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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: 7e-05 |
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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=(0.9,0.98) 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: 30 |
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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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| 4.9606 | 2.45 | 300 | 2.6184 | 1.0 | |
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| 1.4992 | 4.9 | 600 | 0.4233 | 0.4143 | |
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| 0.9757 | 7.35 | 900 | 0.2765 | 0.3021 | |
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| 0.8773 | 9.8 | 1200 | 0.2529 | 0.2528 | |
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| 0.7448 | 12.24 | 1500 | 0.2363 | 0.2258 | |
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| 0.7039 | 14.69 | 1800 | 0.2258 | 0.2103 | |
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| 0.6811 | 17.14 | 2100 | 0.2217 | 0.2074 | |
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| 0.6279 | 19.59 | 2400 | 0.2050 | 0.1915 | |
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| 0.5938 | 22.04 | 2700 | 0.2229 | 0.1922 | |
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| 0.6227 | 24.49 | 3000 | 0.2088 | 0.2019 | |
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| 0.5682 | 26.94 | 3300 | 0.2127 | 0.1874 | |
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| 0.5939 | 29.39 | 3600 | 0.2044 | 0.1789 | |
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| 0.5427 | 31.84 | 3900 | 0.2185 | 0.1791 | |
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| 0.5551 | 34.41 | 4200 | 0.2097 | 0.1644 | |
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| 0.5021 | 36.86 | 4500 | 0.2180 | 0.1678 | |
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| 0.4589 | 39.31 | 4800 | 0.2076 | 0.1581 | |
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| 0.5204 | 41.76 | 5100 | 0.2181 | 0.1587 | |
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| 0.512 | 44.21 | 5400 | 0.2263 | 0.1607 | |
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| 0.465 | 46.66 | 5700 | 0.2204 | 0.1493 | |
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### Framework versions |
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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 |
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