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This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON_VOICE_7_0 - HI dataset. It achieves the following results on the evaluation set:
- Loss: 1.4031
- Wer: 0.6827
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: 7.5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- 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: 2000
- num_epochs: 100.0
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 5.3156 | 3.4 | 500 | 4.5583 | 1.0 |
| 3.3329 | 6.8 | 1000 | 3.4274 | 1.0001 |
| 2.1275 | 10.2 | 1500 | 1.7221 | 0.8763 |
| 1.5737 | 13.6 | 2000 | 1.4188 | 0.8143 |
| 1.3835 | 17.01 | 2500 | 1.2251 | 0.7447 |
| 1.3247 | 20.41 | 3000 | 1.2827 | 0.7394 |
| 1.231 | 23.81 | 3500 | 1.2216 | 0.7074 |
| 1.1819 | 27.21 | 4000 | 1.2210 | 0.6863 |
| 1.1546 | 30.61 | 4500 | 1.3233 | 0.7308 |
| 1.0902 | 34.01 | 5000 | 1.3251 | 0.7010 |
| 1.0749 | 37.41 | 5500 | 1.3274 | 0.7235 |
| 1.0412 | 40.81 | 6000 | 1.2942 | 0.6856 |
| 1.0064 | 44.22 | 6500 | 1.2581 | 0.6732 |
| 1.0006 | 47.62 | 7000 | 1.2767 | 0.6885 |
| 0.9518 | 51.02 | 7500 | 1.2966 | 0.6925 |
| 0.9514 | 54.42 | 8000 | 1.2981 | 0.7067 |
| 0.9241 | 57.82 | 8500 | 1.3835 | 0.7124 |
| 0.9059 | 61.22 | 9000 | 1.3318 | 0.7083 |
| 0.8906 | 64.62 | 9500 | 1.3640 | 0.6962 |
| 0.8468 | 68.03 | 10000 | 1.4727 | 0.6982 |
| 0.8631 | 71.43 | 10500 | 1.3401 | 0.6809 |
| 0.8154 | 74.83 | 11000 | 1.4124 | 0.6955 |
| 0.7953 | 78.23 | 11500 | 1.4245 | 0.6950 |
| 0.818 | 81.63 | 12000 | 1.3944 | 0.6995 |
| 0.7772 | 85.03 | 12500 | 1.3735 | 0.6785 |
| 0.7857 | 88.43 | 13000 | 1.3696 | 0.6808 |
| 0.7705 | 91.84 | 13500 | 1.4101 | 0.6870 |
| 0.7537 | 95.24 | 14000 | 1.4178 | 0.6832 |
| 0.7734 | 98.64 | 14500 | 1.4027 | 0.6831 |
Framework versions
- Transformers 4.16.0.dev0
- Pytorch 1.10.1+cu113
- Datasets 1.18.1.dev0
- Tokenizers 0.11.0
