wav2vec2-base-checkpoint-8
This model is a fine-tuned version of jiobiala24/wav2vec2-base-checkpoint-7.1 on the common_voice dataset. It achieves the following results on the evaluation set:
- Loss: 0.9561
- Wer: 0.3271
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: 0.0001
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 30
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
0.3117 | 1.59 | 1000 | 0.5514 | 0.3451 |
0.2509 | 3.19 | 2000 | 0.5912 | 0.3328 |
0.1918 | 4.78 | 3000 | 0.6103 | 0.3346 |
0.1612 | 6.38 | 4000 | 0.6469 | 0.3377 |
0.1388 | 7.97 | 5000 | 0.6597 | 0.3391 |
0.121 | 9.57 | 6000 | 0.6911 | 0.3472 |
0.1096 | 11.16 | 7000 | 0.7300 | 0.3457 |
0.0959 | 12.76 | 8000 | 0.7660 | 0.3400 |
0.0882 | 14.35 | 9000 | 0.8316 | 0.3394 |
0.0816 | 15.95 | 10000 | 0.8042 | 0.3357 |
0.0739 | 17.54 | 11000 | 0.8087 | 0.3346 |
0.0717 | 19.14 | 12000 | 0.8590 | 0.3353 |
0.066 | 20.73 | 13000 | 0.8750 | 0.3336 |
0.0629 | 22.33 | 14000 | 0.8759 | 0.3333 |
0.0568 | 23.92 | 15000 | 0.8963 | 0.3321 |
0.0535 | 25.52 | 16000 | 0.9391 | 0.3323 |
0.0509 | 27.11 | 17000 | 0.9279 | 0.3296 |
0.0498 | 28.71 | 18000 | 0.9561 | 0.3271 |
Framework versions
- Transformers 4.11.3
- Pytorch 1.10.0+cu111
- Datasets 1.13.3
- Tokenizers 0.10.3
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