wav2vec2-base-finetuned-manthan_base
This model is a fine-tuned version of facebook/wav2vec2-base on the new_dataset dataset. It achieves the following results on the evaluation set:
- Loss: 1.2246
- Accuracy: 0.9691
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: 3e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 2.4725 | 0.98 | 12 | 2.4222 | 0.1057 |
| 2.4501 | 1.98 | 24 | 2.2420 | 0.2784 |
| 2.2977 | 2.98 | 36 | 2.0155 | 0.7603 |
| 2.1331 | 3.98 | 48 | 1.8193 | 0.8582 |
| 1.7927 | 4.98 | 60 | 1.6376 | 0.9459 |
| 1.7226 | 5.98 | 72 | 1.4940 | 0.9613 |
| 1.6036 | 6.98 | 84 | 1.3632 | 0.9665 |
| 1.5181 | 7.98 | 96 | 1.2963 | 0.9562 |
| 1.4384 | 8.98 | 108 | 1.2406 | 0.9742 |
| 1.3339 | 9.98 | 120 | 1.2246 | 0.9691 |
Framework versions
- Transformers 4.19.0
- Pytorch 1.11.0+cu113
- Datasets 1.14.0
- Tokenizers 0.12.1
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