metadata
license: mit
base_model: facebook/w2v-bert-2.0
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: pashto-asr-v3
results: []
pashto-asr-v3
This model is a fine-tuned version of facebook/w2v-bert-2.0 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1448
- Wer: 0.1396
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: 5e-05
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 1300
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
2.9698 | 0.8089 | 100 | 2.8928 | 0.9991 |
0.8095 | 1.6178 | 200 | 0.6035 | 0.4036 |
0.6152 | 2.4267 | 300 | 0.4857 | 0.3593 |
0.3951 | 3.2356 | 400 | 0.4661 | 0.3505 |
0.5493 | 4.0445 | 500 | 0.3651 | 0.2779 |
0.4588 | 4.8534 | 600 | 0.3244 | 0.2632 |
0.3616 | 5.6623 | 700 | 0.2954 | 0.2490 |
0.1938 | 6.4712 | 800 | 0.2655 | 0.2341 |
0.2047 | 7.2801 | 900 | 0.2510 | 0.2022 |
0.2596 | 8.0890 | 1000 | 0.1953 | 0.1756 |
0.1871 | 8.8979 | 1100 | 0.1716 | 0.1642 |
0.0768 | 9.7068 | 1200 | 0.1559 | 0.1554 |
0.1021 | 10.5157 | 1300 | 0.1448 | 0.1396 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1