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w2v-bert-2.0-nepali-iteration-2
kiranpantha/w2v-bert-2.0-nepali-iteration-2
w2v-bert-2.0-nepali-iteration-2 is a automatic speech recognition model from kiranpantha. Use it when you need speech turned into text. It is set up for transformers. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Automatic Speech Recognition
- Library
- transformers
- License
- mit
- Model type
- wav2vec2-bert
- Access
- Public
- Created
- Sep 24, 2024
- Updated
- Sep 24, 2024
- SHA
- 85af3fc9
Base models
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
Wave2Vec2-Bert2.0 - Kiran Pantha
This model is a fine-tuned version of kiranpantha/w2v-bert-2.0-nepali-iteration-test on the OpenSLR54 dataset. It achieves the following results on the evaluation set:
- Loss: 0.4545
- Wer: 0.4636
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: 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: 500
- num_epochs: 2
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.392 | 0.15 | 300 | 0.4561 | 0.4579 |
| 0.5077 | 0.3 | 600 | 0.5402 | 0.5145 |
| 0.5371 | 0.45 | 900 | 0.5083 | 0.4923 |
| 0.4943 | 0.6 | 1200 | 0.5103 | 0.5147 |
| 0.5049 | 0.75 | 1500 | 0.4811 | 0.4752 |
| 0.4809 | 0.9 | 1800 | 0.4751 | 0.4689 |
| 0.4633 | 1.05 | 2100 | 0.5031 | 0.4883 |
| 0.3843 | 1.2 | 2400 | 0.4703 | 0.4573 |
| 0.3753 | 1.35 | 2700 | 0.4542 | 0.4497 |
| 0.356 | 1.5 | 3000 | 0.4510 | 0.4503 |
| 0.3668 | 1.65 | 3300 | 0.4591 | 0.4524 |
| 0.3386 | 1.8 | 3600 | 0.4399 | 0.4459 |
| 0.3452 | 1.95 | 3900 | 0.4545 | 0.4636 |
Framework versions
- Transformers 4.45.0.dev0
- Pytorch 2.4.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- wav2vec2-bert
- License
- mit
- Languages
- ne
- Created
- Sep 24, 2024
- Updated
- Sep 24, 2024