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--- |
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library_name: transformers |
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license: cc-by-nc-4.0 |
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base_model: facebook/mms-1b-all |
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tags: |
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- generated_from_trainer |
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datasets: |
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- fleurs |
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- deepdml/igbo-dict-expansion |
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- deepdml/igbo-dict-expansion-16khz |
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metrics: |
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- wer |
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model-index: |
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- name: wav2vec2-large-mms-1b-igbo |
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results: |
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- task: |
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name: Automatic Speech Recognition |
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type: 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: ig_ng |
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split: test |
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args: ig_ng |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.444900640499261 |
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language: |
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- ig |
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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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# wav2vec2-large-mms-1b-igbo |
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This model is a fine-tuned version of [facebook/mms-1b-all](https://huggingface.co/facebook/mms-1b-all) on the fleurs dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4649 |
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- Wer: 0.4449 |
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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: 0.001 |
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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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 100 |
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- num_epochs: 4 |
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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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| 0.464 | 0.0731 | 1000 | 0.7265 | 0.5768 | |
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| 0.4324 | 0.1463 | 2000 | 0.7455 | 0.6102 | |
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| 0.4307 | 0.2194 | 3000 | 1.1129 | 0.6445 | |
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| 0.3982 | 0.2925 | 4000 | 0.7999 | 0.5870 | |
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| 0.3915 | 0.3657 | 5000 | 0.7252 | 0.5210 | |
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| 0.3834 | 0.4388 | 6000 | 0.7565 | 0.5677 | |
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| 0.376 | 0.5120 | 7000 | 0.7596 | 0.6294 | |
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| 0.388 | 0.5851 | 8000 | 0.6784 | 0.5679 | |
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| 0.3687 | 0.6582 | 9000 | 0.7597 | 0.5916 | |
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| 0.374 | 0.7314 | 10000 | 0.6482 | 0.5023 | |
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| 0.3576 | 0.8045 | 11000 | 0.6486 | 0.5572 | |
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| 0.3621 | 0.8776 | 12000 | 0.5482 | 0.4869 | |
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| 0.363 | 0.9508 | 13000 | 0.6543 | 0.5082 | |
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| 0.3549 | 1.0239 | 14000 | 0.5477 | 0.4849 | |
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| 0.342 | 1.0971 | 15000 | 0.5505 | 0.5079 | |
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| 0.3296 | 1.1702 | 16000 | 0.5701 | 0.5211 | |
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| 0.3363 | 1.2433 | 17000 | 0.5565 | 0.5281 | |
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| 0.3265 | 1.3165 | 18000 | 0.6660 | 0.5794 | |
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| 0.327 | 1.3896 | 19000 | 0.5414 | 0.4854 | |
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| 0.3319 | 1.4627 | 20000 | 0.5677 | 0.5181 | |
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| 0.3273 | 1.5359 | 21000 | 0.5482 | 0.4901 | |
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| 0.3209 | 1.6090 | 22000 | 0.5475 | 0.5019 | |
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| 0.3153 | 1.6821 | 23000 | 0.5278 | 0.4723 | |
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| 0.3214 | 1.7553 | 24000 | 0.5232 | 0.4809 | |
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| 0.3227 | 1.8284 | 25000 | 0.5419 | 0.4950 | |
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| 0.306 | 1.9016 | 26000 | 0.5120 | 0.4653 | |
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| 0.2956 | 1.9747 | 27000 | 0.5043 | 0.4790 | |
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| 0.2875 | 2.0478 | 28000 | 0.5111 | 0.4592 | |
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| 0.3158 | 2.1210 | 29000 | 0.4959 | 0.4582 | |
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| 0.2906 | 2.1941 | 30000 | 0.4857 | 0.4577 | |
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| 0.2985 | 2.2672 | 31000 | 0.4897 | 0.4625 | |
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| 0.2877 | 2.3404 | 32000 | 0.4869 | 0.4667 | |
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| 0.2832 | 2.4135 | 33000 | 0.4877 | 0.4541 | |
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| 0.2815 | 2.4867 | 34000 | 0.4869 | 0.4598 | |
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| 0.28 | 2.5598 | 35000 | 0.4935 | 0.4624 | |
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| 0.2904 | 2.6329 | 36000 | 0.4859 | 0.4540 | |
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| 0.2767 | 2.7061 | 37000 | 0.4879 | 0.4550 | |
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| 0.2801 | 2.7792 | 38000 | 0.4855 | 0.4536 | |
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| 0.2711 | 2.8523 | 39000 | 0.5059 | 0.4674 | |
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| 0.2652 | 2.9255 | 40000 | 0.4715 | 0.4512 | |
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| 0.276 | 2.9986 | 41000 | 0.4804 | 0.4568 | |
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| 0.2556 | 3.0717 | 42000 | 0.4869 | 0.4572 | |
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| 0.275 | 3.1449 | 43000 | 0.4761 | 0.4536 | |
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| 0.2615 | 3.2180 | 44000 | 0.4848 | 0.4679 | |
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| 0.264 | 3.2912 | 45000 | 0.4722 | 0.4518 | |
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| 0.2554 | 3.3643 | 46000 | 0.4747 | 0.4551 | |
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| 0.2632 | 3.4374 | 47000 | 0.4695 | 0.4507 | |
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| 0.2565 | 3.5106 | 48000 | 0.4761 | 0.4506 | |
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| 0.2555 | 3.5837 | 49000 | 0.4802 | 0.4619 | |
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| 0.2397 | 3.6568 | 50000 | 0.4687 | 0.4497 | |
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| 0.2599 | 3.7300 | 51000 | 0.4684 | 0.4506 | |
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| 0.2451 | 3.8031 | 52000 | 0.4678 | 0.4504 | |
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| 0.2623 | 3.8763 | 53000 | 0.4642 | 0.4461 | |
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| 0.2475 | 3.9494 | 54000 | 0.4649 | 0.4449 | |
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### Framework versions |
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- Transformers 4.54.0.dev0 |
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- Pytorch 2.5.1+cu121 |
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- Datasets 3.2.0 |
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- Tokenizers 0.21.0 |
