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--- |
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library_name: transformers |
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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: W2V2_Bert_Afrivoice_FLEURS_Shona_100hr_v1 |
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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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# W2V2_Bert_Afrivoice_FLEURS_Shona_100hr_v1 |
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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 an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2169 |
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- Model Preparation Time: 0.0117 |
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- Wer: 0.2047 |
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- Cer: 0.0377 |
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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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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_ratio: 0.025 |
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- num_epochs: 100 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Model Preparation Time | Wer | Cer | |
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|:-------------:|:-----:|:-----:|:---------------:|:----------------------:|:------:|:------:| |
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| 0.0958 | 1.0 | 4449 | 0.1764 | 0.0117 | 0.2148 | 0.0352 | |
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| 0.093 | 2.0 | 8898 | 0.1879 | 0.0117 | 0.2282 | 0.0382 | |
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| 0.0993 | 3.0 | 13347 | 0.1860 | 0.0117 | 0.2285 | 0.0384 | |
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| 0.0971 | 4.0 | 17796 | 0.1906 | 0.0117 | 0.2379 | 0.0390 | |
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| 0.0912 | 5.0 | 22245 | 0.1843 | 0.0117 | 0.2268 | 0.0381 | |
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| 0.084 | 6.0 | 26694 | 0.1970 | 0.0117 | 0.2247 | 0.0376 | |
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| 0.0786 | 7.0 | 31143 | 0.2031 | 0.0117 | 0.2433 | 0.0419 | |
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| 0.0716 | 8.0 | 35592 | 0.2114 | 0.0117 | 0.2360 | 0.0394 | |
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| 0.0673 | 9.0 | 40041 | 0.2146 | 0.0117 | 0.2358 | 0.0388 | |
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| 0.0617 | 10.0 | 44490 | 0.2282 | 0.0117 | 0.2311 | 0.0384 | |
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| 0.0559 | 11.0 | 48939 | 0.2302 | 0.0117 | 0.2306 | 0.0386 | |
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### Framework versions |
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- Transformers 4.45.2 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 3.0.1 |
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- Tokenizers 0.20.1 |
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