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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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--- |
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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: 0.1438 |
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- Wer: 0.0987 |
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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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| 1.0371 | 1.98 | 525 | 0.1509 | 0.1498 | |
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| 0.0728 | 3.96 | 1050 | 0.1256 | 0.1279 | |
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| 0.0382 | 5.94 | 1575 | 0.1260 | 0.1041 | |
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| 0.0213 | 7.92 | 2100 | 0.1333 | 0.0997 | |
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| 0.0118 | 9.91 | 2625 | 0.1438 | 0.0987 | |
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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 |
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