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--- |
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license: apache-2.0 |
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base_model: facebook/wav2vec2-xls-r-300m |
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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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metrics: |
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- wer |
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model-index: |
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- name: wav2vec2-large-xls-r-300m-dutch-fast-colab |
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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 |
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type: common_voice |
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config: nl |
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split: test |
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args: nl |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.39564262175027465 |
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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-dutch-fast-colab |
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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: 0.5291 |
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- Wer: 0.3956 |
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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: 0.0003 |
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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: 2 |
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- total_train_batch_size: 16 |
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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: 300 |
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- num_epochs: 3 |
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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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| 4.4755 | 0.34 | 200 | 2.9548 | 1.0000 | |
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| 2.1786 | 0.68 | 400 | 1.3052 | 0.8680 | |
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| 0.5853 | 1.02 | 600 | 0.8360 | 0.5886 | |
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| 0.3293 | 1.36 | 800 | 0.7055 | 0.5095 | |
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| 0.2581 | 1.7 | 1000 | 0.6768 | 0.4943 | |
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| 0.2023 | 2.04 | 1200 | 0.5974 | 0.4274 | |
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| 0.1336 | 2.37 | 1400 | 0.5872 | 0.4170 | |
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| 0.1186 | 2.71 | 1600 | 0.5291 | 0.3956 | |
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### Framework versions |
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- Transformers 4.31.0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.4 |
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- Tokenizers 0.13.3 |
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