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--- |
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license: mit |
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base_model: facebook/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: CS224S_Quechua_Project_Bilingual |
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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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# CS224S_Quechua_Project_Bilingual |
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This model is a fine-tuned version of [facebook/w2v-bert-2.0](https://huggingface.co/facebook/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: 0.2367 |
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- Wer: 0.2585 |
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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: 4 |
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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: 8 |
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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: 70 |
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- num_epochs: 5 |
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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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| 1.2273 | 0.3628 | 600 | 0.6478 | 0.6345 | |
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| 0.5989 | 0.7255 | 1200 | 0.4562 | 0.4218 | |
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| 0.4847 | 1.0883 | 1800 | 0.3781 | 0.3914 | |
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| 0.4599 | 1.4510 | 2400 | 0.3657 | 0.3400 | |
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| 0.3462 | 1.8138 | 3000 | 0.3296 | 0.3185 | |
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| 0.3738 | 2.1765 | 3600 | 0.2808 | 0.2975 | |
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| 0.2969 | 2.5393 | 4200 | 0.2856 | 0.2877 | |
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| 0.3985 | 2.9021 | 4800 | 0.2728 | 0.2889 | |
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| 0.2507 | 3.2648 | 5400 | 0.2676 | 0.2732 | |
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| 0.284 | 3.6276 | 6000 | 0.2539 | 0.2553 | |
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| 0.317 | 3.9903 | 6600 | 0.2359 | 0.2496 | |
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| 0.1526 | 4.3531 | 7200 | 0.2444 | 0.2609 | |
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| 0.1813 | 4.7158 | 7800 | 0.2367 | 0.2585 | |
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### Framework versions |
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- Transformers 4.40.2 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.19.2 |
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- Tokenizers 0.19.1 |
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