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w2v-bert-2.0-mt-CV17.0
AigizK/w2v-bert-2.0-mt-CV17.0
w2v-bert-2.0-mt-CV17.0 is a machine learning model from AigizK. 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
- Mar 15, 2025
- Updated
- Mar 15, 2025
- SHA
- bc0b2e42
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-mt-CV17.0
This model is a fine-tuned version of facebook/w2v-bert-2.0 on the common_voice_17_0 dataset. It achieves the following results on the evaluation set:
- eval_loss: 0.1031
- eval_wer: 0.0656
- eval_runtime: 35.2573
- eval_samples_per_second: 16.309
- eval_steps_per_second: 2.042
- epoch: 7.0278
- step: 2400
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: 300
- num_epochs: 10
- mixed_precision_training: Native AMP
Framework versions
- Transformers 4.40.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1
- Type
- wav2vec2-bert
- License
- mit
- Languages
- mt
- Created
- Mar 15, 2025
- Updated
- Mar 15, 2025