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wav2vec2-base-timit-finetune-4-additonal-train
This model is a fine-tuned version of rohitp1/wav2vec2-base-timit-finetune-3 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4123
- Wer: 0.2905
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: 32
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 60
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.1543 | 2.77 | 200 | 0.3600 | 0.3153 |
| 0.1277 | 5.55 | 400 | 0.3621 | 0.3110 |
| 0.106 | 8.33 | 600 | 0.3862 | 0.3050 |
| 0.095 | 11.11 | 800 | 0.4055 | 0.3042 |
| 0.0862 | 13.88 | 1000 | 0.4001 | 0.3083 |
| 0.0834 | 16.66 | 1200 | 0.4228 | 0.2993 |
| 0.0676 | 19.44 | 1400 | 0.4245 | 0.2955 |
| 0.0593 | 22.22 | 1600 | 0.4123 | 0.2905 |
Framework versions
- Transformers 4.24.0
- Pytorch 1.12.1
- Datasets 2.7.0
- Tokenizers 0.11.0
