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--- |
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base_model: facebook/wav2vec2-xls-r-300m |
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datasets: |
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- fleurs |
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library_name: transformers |
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license: apache-2.0 |
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metrics: |
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- wer |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: wav2vec2-xls-r-Wolof-20-hours-alffa-plus-fleurs-dataset |
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results: |
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- task: |
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type: automatic-speech-recognition |
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name: Automatic Speech Recognition |
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dataset: |
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name: fleurs |
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type: fleurs |
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config: wo_sn |
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split: None |
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args: wo_sn |
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metrics: |
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- type: wer |
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value: 0.423307335820052 |
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name: Wer |
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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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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/asr-africa-research-team/ASR%20Africa/runs/m728q8fb) |
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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/asr-africa-research-team/ASR%20Africa/runs/m728q8fb) |
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# wav2vec2-xls-r-Wolof-20-hours-alffa-plus-fleurs-dataset |
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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 fleurs dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.2175 |
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- Wer: 0.4233 |
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- Cer: 0.1476 |
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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: 16 |
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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: 32 |
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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_ratio: 0.1 |
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- num_epochs: 50 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Wer | Cer | |
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|:-------------:|:-------:|:-----:|:---------------:|:------:|:------:| |
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| 2.7783 | 1.2365 | 400 | 1.5400 | 0.8840 | 0.3321 | |
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| 0.9198 | 2.4730 | 800 | 0.8296 | 0.6037 | 0.2088 | |
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| 0.6527 | 3.7094 | 1200 | 0.8048 | 0.5326 | 0.1865 | |
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| 0.5793 | 4.9459 | 1600 | 0.7323 | 0.5155 | 0.1849 | |
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| 0.5234 | 6.1824 | 2000 | 0.6832 | 0.5016 | 0.1782 | |
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| 0.4583 | 7.4189 | 2400 | 0.7613 | 0.4925 | 0.1770 | |
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| 0.4251 | 8.6553 | 2800 | 0.6324 | 0.4951 | 0.1750 | |
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| 0.3763 | 9.8918 | 3200 | 0.7067 | 0.4810 | 0.1697 | |
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| 0.3503 | 11.1283 | 3600 | 0.7494 | 0.5030 | 0.1767 | |
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| 0.325 | 12.3648 | 4000 | 0.6757 | 0.4997 | 0.1734 | |
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| 0.288 | 13.6012 | 4400 | 0.6880 | 0.4851 | 0.1679 | |
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| 0.2673 | 14.8377 | 4800 | 0.6832 | 0.5268 | 0.1930 | |
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| 0.2485 | 16.0742 | 5200 | 0.6879 | 0.4730 | 0.1726 | |
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| 0.2229 | 17.3107 | 5600 | 0.7245 | 0.4907 | 0.1727 | |
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| 0.2088 | 18.5471 | 6000 | 0.7458 | 0.4642 | 0.1626 | |
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| 0.1903 | 19.7836 | 6400 | 0.7750 | 0.4572 | 0.1610 | |
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| 0.1767 | 21.0201 | 6800 | 0.8254 | 0.4550 | 0.1606 | |
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| 0.1613 | 22.2566 | 7200 | 0.7481 | 0.4613 | 0.1600 | |
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| 0.1554 | 23.4930 | 7600 | 0.8343 | 0.4425 | 0.1573 | |
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| 0.1429 | 24.7295 | 8000 | 0.8984 | 0.4465 | 0.1590 | |
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| 0.1384 | 25.9660 | 8400 | 0.7643 | 0.4624 | 0.1649 | |
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| 0.1295 | 27.2025 | 8800 | 0.8534 | 0.4489 | 0.1568 | |
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| 0.1178 | 28.4389 | 9200 | 0.9115 | 0.4481 | 0.1587 | |
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| 0.1146 | 29.6754 | 9600 | 0.8835 | 0.4403 | 0.1565 | |
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| 0.1033 | 30.9119 | 10000 | 0.9292 | 0.4525 | 0.1575 | |
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| 0.0957 | 32.1484 | 10400 | 1.0917 | 0.4407 | 0.1526 | |
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| 0.0944 | 33.3849 | 10800 | 0.9554 | 0.4474 | 0.1573 | |
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| 0.0878 | 34.6213 | 11200 | 1.0647 | 0.4385 | 0.1531 | |
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| 0.0828 | 35.8578 | 11600 | 1.0365 | 0.4356 | 0.1512 | |
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| 0.0821 | 37.0943 | 12000 | 1.0613 | 0.4461 | 0.1571 | |
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| 0.0736 | 38.3308 | 12400 | 1.0852 | 0.4333 | 0.1521 | |
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| 0.0701 | 39.5672 | 12800 | 1.0551 | 0.4334 | 0.1518 | |
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| 0.0677 | 40.8037 | 13200 | 1.1009 | 0.4327 | 0.1500 | |
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| 0.0645 | 42.0402 | 13600 | 1.1279 | 0.4277 | 0.1490 | |
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| 0.0607 | 43.2767 | 14000 | 1.1581 | 0.4214 | 0.1483 | |
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| 0.0593 | 44.5131 | 14400 | 1.2038 | 0.4231 | 0.1473 | |
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| 0.0557 | 45.7496 | 14800 | 1.1791 | 0.4249 | 0.1525 | |
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| 0.0554 | 46.9861 | 15200 | 1.2012 | 0.4248 | 0.1484 | |
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| 0.0543 | 48.2226 | 15600 | 1.2087 | 0.4232 | 0.1471 | |
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| 0.0525 | 49.4590 | 16000 | 1.2175 | 0.4233 | 0.1476 | |
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### Framework versions |
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- Transformers 4.44.1 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.17.0 |
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- Tokenizers 0.19.1 |
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