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STT_Model_8
This model is a fine-tuned version of facebook/wav2vec2-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5858
- Wer: 0.3549
Model description
More information needed
Intended uses & limitations
More information needed
Dataset info
- Name: LJSpeech
- Source: https://www.kaggle.com/datasets/mathurinache/the-lj-speech-dataset
- Total audios (in Google Drive): 1420
- Total transcripts (in Google Drive): 13100
- No. of rows selected: 100
- Train-test ratio: 80:20
- No. of training set: 80
- No. of testing set: 20
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: 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: 100
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| No log | 20.0 | 200 | 2.9443 | 1.0 |
| No log | 40.0 | 400 | 2.8603 | 1.0 |
| 3.8362 | 60.0 | 600 | 0.5940 | 0.4197 |
| 3.8362 | 80.0 | 800 | 0.5702 | 0.3380 |
| 0.2307 | 100.0 | 1000 | 0.5858 | 0.3549 |
Framework versions
- Transformers 4.26.0
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2
