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hindi_beekeeping_wav2vec2-2
TheAIchemist13/hindi_beekeeping_wav2vec2-2
hindi_beekeeping_wav2vec2-2 is a automatic speech recognition model from TheAIchemist13. Use it when you need speech turned into text. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Automatic Speech Recognition
- Library
- transformers
- License
- apache-2.0
- Model type
- wav2vec2
- Access
- Public
- Created
- Oct 17, 2023
- Updated
- Oct 19, 2023
- SHA
- c30e47d4
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. -->
hindi_beekeeping_wav2vec2-2
This model is a fine-tuned version of Harveenchadha/hindi_base_wav2vec2 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.5244
- Wer: 0.3984
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: 0.0003
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- 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: 10
- num_epochs: 100
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.3815 | 4.55 | 25 | 1.0849 | 0.3984 |
| 0.1143 | 9.09 | 50 | 1.0752 | 0.3659 |
| 0.0827 | 13.64 | 75 | 1.4514 | 0.4390 |
| 0.0546 | 18.18 | 100 | 1.6510 | 0.4146 |
| 0.0506 | 22.73 | 125 | 1.5120 | 0.4593 |
| 0.0394 | 27.27 | 150 | 1.5948 | 0.4797 |
| 0.0356 | 31.82 | 175 | 1.4317 | 0.4228 |
| 0.0314 | 36.36 | 200 | 1.7475 | 0.4553 |
| 0.0278 | 40.91 | 225 | 1.6500 | 0.4634 |
| 0.0335 | 45.45 | 250 | 1.5310 | 0.4756 |
| 0.0213 | 50.0 | 275 | 1.4817 | 0.4593 |
| 0.0177 | 54.55 | 300 | 1.6921 | 0.4228 |
| 0.0115 | 59.09 | 325 | 1.6241 | 0.4106 |
| 0.0152 | 63.64 | 350 | 1.5167 | 0.4106 |
| 0.0109 | 68.18 | 375 | 1.7510 | 0.4553 |
| 0.011 | 72.73 | 400 | 1.6425 | 0.4146 |
| 0.0101 | 77.27 | 425 | 1.6253 | 0.4146 |
| 0.0091 | 81.82 | 450 | 1.6383 | 0.3984 |
| 0.008 | 86.36 | 475 | 1.5251 | 0.3984 |
| 0.0069 | 90.91 | 500 | 1.5244 | 0.3984 |
Framework versions
- Transformers 4.34.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- wav2vec2
- License
- apache-2.0
- Created
- Oct 17, 2023
- Updated
- Oct 19, 2023