wav2vec-sq-3.0
This model is a fine-tuned version of facebook/wav2vec2-large-xlsr-53 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.9327
- Wer: 0.6953
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: 1e-05
- train_batch_size: 32
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 250
- training_steps: 2500
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
6.166 | 0.2657 | 250 | 2.9837 | 1.0 |
5.9696 | 0.5313 | 500 | 2.8618 | 1.0 |
5.1332 | 0.7970 | 750 | 2.0889 | 0.9683 |
3.6118 | 1.0627 | 1000 | 1.4413 | 0.8753 |
2.6843 | 1.3284 | 1250 | 1.1732 | 0.8004 |
2.3974 | 1.5940 | 1500 | 1.0998 | 0.7510 |
2.2139 | 1.8597 | 1750 | 1.0167 | 0.7115 |
2.0901 | 2.1254 | 2000 | 0.9646 | 0.7069 |
2.0002 | 2.3911 | 2250 | 0.9416 | 0.6906 |
1.9739 | 2.6567 | 2500 | 0.9327 | 0.6953 |
Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0
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Model tree for akadriu/wav2vec-sq-3.0
Base model
facebook/wav2vec2-large-xlsr-53