wav2vec2-base-checkpoint-5
This model is a fine-tuned version of jiobiala24/wav2vec2-base-checkpoint-4 on the common_voice dataset. It achieves the following results on the evaluation set:
- Loss: 0.9849
- Wer: 0.3354
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 |
---|---|---|---|---|
0.3947 | 1.96 | 1000 | 0.5749 | 0.3597 |
0.2856 | 3.93 | 2000 | 0.6212 | 0.3479 |
0.221 | 5.89 | 3000 | 0.6280 | 0.3502 |
0.1755 | 7.86 | 4000 | 0.6517 | 0.3526 |
0.1452 | 9.82 | 5000 | 0.7115 | 0.3481 |
0.1256 | 11.79 | 6000 | 0.7687 | 0.3509 |
0.1117 | 13.75 | 7000 | 0.7785 | 0.3490 |
0.0983 | 15.72 | 8000 | 0.8115 | 0.3442 |
0.0877 | 17.68 | 9000 | 0.8290 | 0.3429 |
0.0799 | 19.65 | 10000 | 0.8517 | 0.3412 |
0.0733 | 21.61 | 11000 | 0.9370 | 0.3448 |
0.066 | 23.58 | 12000 | 0.9157 | 0.3410 |
0.0623 | 25.54 | 13000 | 0.9673 | 0.3377 |
0.0583 | 27.5 | 14000 | 0.9804 | 0.3348 |
0.0544 | 29.47 | 15000 | 0.9849 | 0.3354 |
Framework versions
- Transformers 4.11.3
- Pytorch 1.10.0+cu111
- Datasets 1.13.3
- Tokenizers 0.10.3
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