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w2v-bert-2.0-mongolian-colab-CV16.0
rkadyan/w2v-bert-2.0-mongolian-colab-CV16.0
w2v-bert-2.0-mongolian-colab-CV16.0 is a machine learning model from rkadyan. 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 9, 2024
- Updated
- Aug 9, 2024
- SHA
- 7430a47c
Base models
Datasets
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. -->
w2v-bert-2.0-mongolian-colab-CV16.0
This model is a fine-tuned version of facebook/w2v-bert-2.0 on the common_voice_16_0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.5145
- Wer: 0.3243
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: 500
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 1.8274 | 2.3715 | 300 | 0.6386 | 0.5269 |
| 0.3402 | 4.7431 | 600 | 0.5916 | 0.4212 |
| 0.1732 | 7.1146 | 900 | 0.5562 | 0.3816 |
| 0.0731 | 9.4862 | 1200 | 0.5145 | 0.3243 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
- Type
- wav2vec2-bert
- License
- mit
- Created
- Aug 9, 2024
- Updated
- Aug 9, 2024