w2v2-base-pretrained_lr1e-4_at0.8_da0.5
This model is a fine-tuned version of facebook/wav2vec2-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 12.5971
- Wer: 1.0
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
- training_steps: 3500
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
22.3588 | 10.87 | 250 | 23.6457 | 1.0 |
8.9908 | 21.74 | 500 | 12.4169 | 1.0 |
11.1075 | 32.61 | 750 | 20.5658 | 1.0 |
13.3015 | 43.48 | 1000 | 20.3357 | 1.0 |
10.7105 | 54.35 | 1250 | 12.4533 | 1.0 |
8.8951 | 65.22 | 1500 | 12.5400 | 1.0 |
8.8229 | 76.09 | 1750 | 12.5416 | 1.0 |
8.7878 | 86.96 | 2000 | 12.5533 | 1.0 |
8.8351 | 97.83 | 2250 | 12.5107 | 1.0 |
8.8182 | 108.7 | 2500 | 12.6065 | 1.0 |
8.7863 | 119.57 | 2750 | 12.6950 | 1.0 |
8.801 | 130.43 | 3000 | 12.6095 | 1.0 |
8.8417 | 141.3 | 3250 | 12.6030 | 1.0 |
8.7401 | 152.17 | 3500 | 12.5971 | 1.0 |
Framework versions
- Transformers 4.35.0
- Pytorch 2.0.0
- Datasets 2.14.6
- Tokenizers 0.14.1
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