w2v-bert-2.0-malayalam-colab-CV17.0
This model is a fine-tuned version of facebook/w2v-bert-2.0 on the common_voice_17_0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.7416
- Wer: 0.4932
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: 3e-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_ratio: 0.15
- training_steps: 2000
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
3.8561 | 3.1496 | 200 | 0.7115 | 0.7843 |
0.3748 | 6.2992 | 400 | 0.5012 | 0.5954 |
0.1826 | 9.4488 | 600 | 0.4939 | 0.5616 |
0.1032 | 12.5984 | 800 | 0.5389 | 0.5467 |
0.0578 | 15.7480 | 1000 | 0.5683 | 0.5313 |
0.0264 | 18.8976 | 1200 | 0.6533 | 0.5087 |
0.0097 | 22.0472 | 1400 | 0.6600 | 0.5055 |
0.0032 | 25.1969 | 1600 | 0.6981 | 0.4965 |
0.0015 | 28.3465 | 1800 | 0.7326 | 0.4984 |
0.0011 | 31.4961 | 2000 | 0.7416 | 0.4932 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
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Base model
facebook/w2v-bert-2.0