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malayalam_combined_Extempore
asr-malayalam/malayalam_combined_Extempore
malayalam_combined_Extempore is a machine learning model from asr-malayalam. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
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At a glance
- License
- mit
- Model type
- wav2vec2-bert
- Access
- Public
- Created
- Aug 20, 2024
- Updated
- Aug 21, 2024
- SHA
- ac65a53a
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. -->
malayalam_combined_Extempore
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: 0.4866
- Wer: 0.4837
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: 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: 50
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.8139 | 0.9794 | 500 | 0.8389 | 0.6821 |
| 0.6539 | 1.9589 | 1000 | 0.6815 | 0.6041 |
| 0.5383 | 2.9383 | 1500 | 0.5827 | 0.5705 |
| 0.4772 | 3.9177 | 2000 | 0.5398 | 0.5548 |
| 0.4351 | 4.8972 | 2500 | 0.5342 | 0.5407 |
| 0.3866 | 5.8766 | 3000 | 0.5411 | 0.5174 |
| 0.3567 | 6.8560 | 3500 | 0.5063 | 0.5085 |
| 0.3047 | 7.8355 | 4000 | 0.4886 | 0.4986 |
| 0.2879 | 8.8149 | 4500 | 0.4878 | 0.4884 |
| 0.2648 | 9.7943 | 5000 | 0.4866 | 0.4837 |
Framework versions
- Transformers 4.43.0.dev0
- Pytorch 1.14.0a0+44dac51
- Datasets 2.16.1
- Tokenizers 0.19.1
- Type
- wav2vec2-bert
- License
- mit
- Created
- Aug 20, 2024
- Updated
- Aug 21, 2024