wav2vec2-mms-1b-malayalam-colab-CV17.0-v2
This model is a fine-tuned version of facebook/mms-1b-all on the common_voice_17_0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.2965
- Wer: 0.5284
- Cer: 0.0934
- Bleu: 0.1997
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: 0.001
- 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_ratio: 0.15
- training_steps: 2000
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer | Cer | Bleu |
---|---|---|---|---|---|---|
5.5563 | 3.1496 | 200 | 0.3157 | 0.5580 | 0.1055 | 0.1800 |
0.3888 | 6.2992 | 400 | 0.2983 | 0.5471 | 0.1003 | 0.1906 |
0.3328 | 9.4488 | 600 | 0.3008 | 0.5542 | 0.1002 | 0.1634 |
0.3006 | 12.5984 | 800 | 0.2821 | 0.5368 | 0.0984 | 0.1888 |
0.2743 | 15.7480 | 1000 | 0.2913 | 0.5329 | 0.0968 | 0.1813 |
0.2461 | 18.8976 | 1200 | 0.2822 | 0.5319 | 0.0957 | 0.1937 |
0.2346 | 22.0472 | 1400 | 0.2933 | 0.5335 | 0.0942 | 0.1848 |
0.2112 | 25.1969 | 1600 | 0.2885 | 0.5300 | 0.0947 | 0.1900 |
0.2006 | 28.3465 | 1800 | 0.2944 | 0.5329 | 0.0939 | 0.1870 |
0.1879 | 31.4961 | 2000 | 0.2965 | 0.5284 | 0.0934 | 0.1997 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
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Model tree for ndeclarke/wav2vec2-mms-1b-malayalam-colab-CV17.0-v2
Base model
facebook/mms-1b-allEvaluation results
- Wer on common_voice_17_0test set self-reported0.528
- Bleu on common_voice_17_0test set self-reported0.200