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base-model-with-warmup-fulldata-fairseq-V1
This model is a fine-tuned version of facebook/wav2vec2-base-960h on the None dataset. It achieves the following results on the evaluation set:
- Loss: 4.6583
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: 8
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.98) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 200
- num_epochs: 50
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
15.6587 | 2.05 | 200 | 4.4816 |
3.8464 | 4.1 | 400 | 4.7516 |
3.8377 | 6.15 | 600 | 4.4104 |
3.915 | 8.21 | 800 | 4.6832 |
3.8094 | 10.26 | 1000 | 5.1651 |
3.8095 | 12.31 | 1200 | 4.7847 |
3.8427 | 14.36 | 1400 | 4.6613 |
3.7917 | 16.41 | 1600 | 4.7898 |
3.804 | 18.46 | 1800 | 4.7368 |
3.8492 | 20.51 | 2000 | 4.7656 |
3.7943 | 22.56 | 2200 | 4.8043 |
3.7982 | 24.62 | 2400 | 4.5903 |
3.7979 | 26.67 | 2600 | 4.5546 |
3.7938 | 28.72 | 2800 | 4.6392 |
3.7891 | 30.77 | 3000 | 4.8080 |
3.7936 | 32.82 | 3200 | 4.5811 |
3.7926 | 34.87 | 3400 | 4.5891 |
3.7922 | 36.92 | 3600 | 4.6251 |
3.79 | 38.97 | 3800 | 4.7409 |
3.791 | 41.03 | 4000 | 4.6539 |
3.7893 | 43.08 | 4200 | 4.6752 |
3.7882 | 45.13 | 4400 | 4.6751 |
3.7924 | 47.18 | 4600 | 4.6222 |
3.7991 | 49.23 | 4800 | 4.6583 |
Framework versions
- Transformers 4.28.0
- Pytorch 2.0.1
- Datasets 2.12.0
- Tokenizers 0.13.2