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--- |
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base_model: ylacombe/w2v-bert-2.0 |
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tags: |
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- generated_from_trainer |
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metrics: |
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- wer |
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model-index: |
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- name: w2v-bert-2.0-ukrainian-colab-CV16.0 |
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results: |
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- task: |
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name: Speech Recognition |
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type: automatic-speech-recognition |
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dataset: |
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name: Common Voice uk |
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type: common_voice |
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args: uk |
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metrics: |
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- name: Test WER |
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type: wer |
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value: 9.81 |
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license: mit |
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datasets: |
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- common_voice |
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language: |
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- uk |
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pipeline_tag: automatic-speech-recognition |
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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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# w2v-bert-2.0-ukrainian-colab-CV16.0 |
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This model is a fine-tuned version of [ylacombe/w2v-bert-2.0](https://huggingface.co/ylacombe/w2v-bert-2.0) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1386 |
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- Wer: 0.0981 |
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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: 5e-05 |
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- train_batch_size: 64 |
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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: 128 |
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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: 500 |
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- num_epochs: 10 |
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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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| 0.8074 | 1.98 | 520 | 0.1498 | 0.1461 | |
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| 0.0694 | 3.96 | 1040 | 0.1243 | 0.1213 | |
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| 0.0369 | 5.94 | 1560 | 0.1221 | 0.1059 | |
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| 0.0214 | 7.92 | 2080 | 0.1257 | 0.0987 | |
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| 0.0115 | 9.9 | 2600 | 0.1386 | 0.0981 | |
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### Framework versions |
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- Transformers 4.37.0.dev0 |
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- Pytorch 1.12.1+cu116 |
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- Datasets 2.4.0 |
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- Tokenizers 0.15.1 |
