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wav2vec2-large-mn-pretrain-42h-100-epochs
This model is a fine-tuned version of bayartsogt/wav2vec2-large-mn-pretrain-42h on the common_voice dataset. It achieves the following results on the evaluation set:
- Loss: 6.4172
- Wer: 1.0
- Cer: 0.9841
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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 10000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|---|---|---|---|---|---|
| 7.6418 | 1.59 | 400 | 6.4239 | 1.0 | 0.9841 |
| 5.5936 | 3.19 | 800 | 6.4154 | 1.0 | 0.9841 |
| 5.5208 | 4.78 | 1200 | 6.5248 | 1.0 | 0.9841 |
| 5.4869 | 6.37 | 1600 | 6.3805 | 1.0 | 0.9841 |
| 5.4757 | 7.97 | 2000 | 6.3988 | 1.0 | 0.9841 |
| 5.4624 | 9.56 | 2400 | 6.4058 | 1.0 | 0.9841 |
| 5.517 | 11.16 | 2800 | 6.3991 | 1.0 | 0.9841 |
| 5.4821 | 12.75 | 3200 | 6.4066 | 1.0 | 0.9841 |
| 5.487 | 14.34 | 3600 | 6.4281 | 1.0 | 0.9841 |
| 5.4786 | 15.93 | 4000 | 6.4174 | 1.0 | 0.9841 |
| 5.5017 | 17.53 | 4400 | 6.4338 | 1.0 | 0.9841 |
| 5.4967 | 19.12 | 4800 | 6.4653 | 1.0 | 0.9841 |
| 5.4619 | 20.72 | 5200 | 6.4499 | 1.0 | 0.9841 |
| 5.4883 | 22.31 | 5600 | 6.4345 | 1.0 | 0.9841 |
| 5.4899 | 23.9 | 6000 | 6.4224 | 1.0 | 0.9841 |
| 5.493 | 25.5 | 6400 | 6.4374 | 1.0 | 0.9841 |
| 5.4549 | 27.09 | 6800 | 6.4320 | 1.0 | 0.9841 |
| 5.4531 | 28.68 | 7200 | 6.4137 | 1.0 | 0.9841 |
| 5.4738 | 30.28 | 7600 | 6.4155 | 1.0 | 0.9841 |
| 5.4309 | 31.87 | 8000 | 6.4193 | 1.0 | 0.9841 |
| 5.4669 | 33.47 | 8400 | 6.4109 | 1.0 | 0.9841 |
| 5.47 | 35.06 | 8800 | 6.4111 | 1.0 | 0.9841 |
| 5.4623 | 36.65 | 9200 | 6.4102 | 1.0 | 0.9841 |
| 5.4583 | 38.25 | 9600 | 6.4150 | 1.0 | 0.9841 |
| 5.4551 | 39.84 | 10000 | 6.4172 | 1.0 | 0.9841 |
Framework versions
- Transformers 4.20.1
- Pytorch 1.11.0
- Datasets 2.1.0
- Tokenizers 0.12.1
