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wav2vec2-large-xls-r-300m-amharic-ASR-final
timotewos/wav2vec2-large-xls-r-300m-amharic-ASR-final
wav2vec2-large-xls-r-300m-amharic-ASR-final is a machine learning model from timotewos. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- License
- apache-2.0
- Model type
- wav2vec2
- Access
- Public
- Created
- Dec 10, 2024
- Updated
- Dec 11, 2024
- SHA
- 4daefd4b
Base models
Datasets
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
wav2vec2-large-xls-r-300m-amharic-ASR-final
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the common_voice_16_1 dataset. It achieves the following results on the evaluation set:
- Loss: 1.8430
- Wer: 0.9093
- Cer: 0.3582
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0003
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 80
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|---|---|---|---|---|---|
| 12.9379 | 5.0 | 100 | 4.1617 | 1.0 | 0.9997 |
| 4.0909 | 10.0 | 200 | 4.0177 | 1.0 | 0.9531 |
| 3.9876 | 15.0 | 300 | 3.9620 | 1.0 | 0.9404 |
| 3.9269 | 20.0 | 400 | 3.9533 | 0.9987 | 0.9172 |
| 3.095 | 25.0 | 500 | 2.1131 | 1.0173 | 0.5117 |
| 0.9792 | 30.0 | 600 | 1.7629 | 0.9373 | 0.4255 |
| 0.4635 | 35.0 | 700 | 1.8393 | 0.9560 | 0.4060 |
| 0.3034 | 40.0 | 800 | 1.8041 | 0.9099 | 0.3959 |
| 0.2285 | 45.0 | 900 | 1.8211 | 0.9173 | 0.3769 |
| 0.189 | 50.0 | 1000 | 1.8982 | 0.9306 | 0.3854 |
| 0.1692 | 55.0 | 1100 | 1.8831 | 0.9393 | 0.3795 |
| 0.1511 | 60.0 | 1200 | 1.8967 | 0.9346 | 0.3739 |
| 0.1326 | 65.0 | 1300 | 1.9037 | 0.9420 | 0.3823 |
| 0.1185 | 70.0 | 1400 | 1.8853 | 0.9146 | 0.3653 |
| 0.1102 | 75.0 | 1500 | 1.8515 | 0.9079 | 0.3598 |
| 0.1059 | 80.0 | 1600 | 1.8430 | 0.9093 | 0.3582 |
Framework versions
- Transformers 4.42.0
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
- Type
- wav2vec2
- License
- apache-2.0
- Created
- Dec 10, 2024
- Updated
- Dec 11, 2024