malayalam_combined_Extempore
This model is a fine-tuned version of facebook/w2v-bert-2.0 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4866
- Wer: 0.4837
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: 5e-05
- 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: 50
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
0.8139 | 0.9794 | 500 | 0.8389 | 0.6821 |
0.6539 | 1.9589 | 1000 | 0.6815 | 0.6041 |
0.5383 | 2.9383 | 1500 | 0.5827 | 0.5705 |
0.4772 | 3.9177 | 2000 | 0.5398 | 0.5548 |
0.4351 | 4.8972 | 2500 | 0.5342 | 0.5407 |
0.3866 | 5.8766 | 3000 | 0.5411 | 0.5174 |
0.3567 | 6.8560 | 3500 | 0.5063 | 0.5085 |
0.3047 | 7.8355 | 4000 | 0.4886 | 0.4986 |
0.2879 | 8.8149 | 4500 | 0.4878 | 0.4884 |
0.2648 | 9.7943 | 5000 | 0.4866 | 0.4837 |
Framework versions
- Transformers 4.43.0.dev0
- Pytorch 1.14.0a0+44dac51
- Datasets 2.16.1
- Tokenizers 0.19.1
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Model tree for asr-malayalam/malayalam_combined_Extempore
Base model
facebook/w2v-bert-2.0