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hello_2b_3
This model is a fine-tuned version of facebook/wav2vec2-xls-r-2b on the COMMON_VOICE - TR dataset. It achieves the following results on the evaluation set:
- Loss: 1.5615
- Wer: 0.9808
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-06
- train_batch_size: 2
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 8
- total_train_batch_size: 32
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 30.0
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 3.6389 | 0.92 | 100 | 3.6218 | 1.0 |
| 1.6676 | 1.85 | 200 | 3.2655 | 1.0 |
| 0.3067 | 2.77 | 300 | 3.2273 | 1.0 |
| 0.1924 | 3.7 | 400 | 3.0238 | 0.9999 |
| 0.1777 | 4.63 | 500 | 2.1606 | 0.9991 |
| 0.1481 | 5.55 | 600 | 1.8742 | 0.9982 |
| 0.1128 | 6.48 | 700 | 2.0114 | 0.9994 |
| 0.1806 | 7.4 | 800 | 1.9032 | 0.9984 |
| 0.0399 | 8.33 | 900 | 2.0556 | 0.9996 |
| 0.0729 | 9.26 | 1000 | 2.0515 | 0.9987 |
| 0.0847 | 10.18 | 1100 | 2.2121 | 0.9995 |
| 0.0777 | 11.11 | 1200 | 1.7002 | 0.9923 |
| 0.0476 | 12.04 | 1300 | 1.5262 | 0.9792 |
| 0.0518 | 12.96 | 1400 | 1.5990 | 0.9832 |
| 0.071 | 13.88 | 1500 | 1.6326 | 0.9875 |
| 0.0333 | 14.81 | 1600 | 1.5955 | 0.9870 |
| 0.0369 | 15.74 | 1700 | 1.5577 | 0.9832 |
| 0.0689 | 16.66 | 1800 | 1.5415 | 0.9839 |
| 0.0227 | 17.59 | 1900 | 1.5450 | 0.9878 |
| 0.0472 | 18.51 | 2000 | 1.5642 | 0.9846 |
| 0.0214 | 19.44 | 2100 | 1.6103 | 0.9846 |
| 0.0289 | 20.37 | 2200 | 1.6467 | 0.9898 |
| 0.0182 | 21.29 | 2300 | 1.5268 | 0.9780 |
| 0.0439 | 22.22 | 2400 | 1.6001 | 0.9818 |
| 0.06 | 23.15 | 2500 | 1.5481 | 0.9813 |
| 0.0351 | 24.07 | 2600 | 1.5672 | 0.9820 |
| 0.0198 | 24.99 | 2700 | 1.6303 | 0.9856 |
| 0.0328 | 25.92 | 2800 | 1.5958 | 0.9831 |
| 0.0245 | 26.85 | 2900 | 1.5745 | 0.9809 |
| 0.0885 | 27.77 | 3000 | 1.5455 | 0.9809 |
| 0.0224 | 28.7 | 3100 | 1.5378 | 0.9824 |
| 0.0223 | 29.63 | 3200 | 1.5642 | 0.9810 |
Framework versions
- Transformers 4.13.0.dev0
- Pytorch 1.10.0
- Datasets 1.15.2.dev0
- Tokenizers 0.10.3
