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w2v-bert-2.0-dhivehi-cv-v3

Serialtechlab / w2v-bert-2.0-dhivehi-cv-v3

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Total runs: 0
24-hour runs: 0
7-day runs: 0
30-day runs: 0
Model's Last Updated: December 29 2025
automatic-speech-recognition

Introduction of w2v-bert-2.0-dhivehi-cv-v3

Model Details of w2v-bert-2.0-dhivehi-cv-v3

w2v-bert-2.0-dhivehi-cv-v3

This model is a fine-tuned version of Serialtechlab/w2v-bert-2.0-dhivehi-cv on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2093
  • Wer: 0.3803
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-06
  • train_batch_size: 4
  • eval_batch_size: 4
  • seed: 42
  • gradient_accumulation_steps: 8
  • total_train_batch_size: 32
  • optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • num_epochs: 5
  • mixed_precision_training: Native AMP
Training results
Training Loss Epoch Step Validation Loss Wer
0.2923 0.6193 500 0.2912 0.4345
0.2363 1.2378 1000 0.2447 0.4031
0.224 1.8571 1500 0.2216 0.4003
0.1901 2.4756 2000 0.2228 0.3953
0.1633 3.0941 2500 0.2121 0.3889
0.1636 3.7134 3000 0.2142 0.3868
0.1515 4.3319 3500 0.2111 0.3875
0.1355 4.9512 4000 0.2093 0.3803
Framework versions
  • Transformers 4.57.3
  • Pytorch 2.9.1+cu128
  • Datasets 4.4.2
  • Tokenizers 0.22.1

Runs of Serialtechlab w2v-bert-2.0-dhivehi-cv-v3 on huggingface.co

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3-day runs
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7-day runs
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More Information About w2v-bert-2.0-dhivehi-cv-v3 huggingface.co Model

w2v-bert-2.0-dhivehi-cv-v3 huggingface.co

w2v-bert-2.0-dhivehi-cv-v3 huggingface.co is an AI model on huggingface.co that provides w2v-bert-2.0-dhivehi-cv-v3's model effect (), which can be used instantly with this Serialtechlab w2v-bert-2.0-dhivehi-cv-v3 model. huggingface.co supports a free trial of the w2v-bert-2.0-dhivehi-cv-v3 model, and also provides paid use of the w2v-bert-2.0-dhivehi-cv-v3. Support call w2v-bert-2.0-dhivehi-cv-v3 model through api, including Node.js, Python, http.

w2v-bert-2.0-dhivehi-cv-v3 huggingface.co Url

https://huggingface.co/Serialtechlab/w2v-bert-2.0-dhivehi-cv-v3

Serialtechlab w2v-bert-2.0-dhivehi-cv-v3 online free

w2v-bert-2.0-dhivehi-cv-v3 huggingface.co is an online trial and call api platform, which integrates w2v-bert-2.0-dhivehi-cv-v3's modeling effects, including api services, and provides a free online trial of w2v-bert-2.0-dhivehi-cv-v3, you can try w2v-bert-2.0-dhivehi-cv-v3 online for free by clicking the link below.

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https://huggingface.co/Serialtechlab/w2v-bert-2.0-dhivehi-cv-v3

w2v-bert-2.0-dhivehi-cv-v3 install

w2v-bert-2.0-dhivehi-cv-v3 is an open source model from GitHub that offers a free installation service, and any user can find w2v-bert-2.0-dhivehi-cv-v3 on GitHub to install. At the same time, huggingface.co provides the effect of w2v-bert-2.0-dhivehi-cv-v3 install, users can directly use w2v-bert-2.0-dhivehi-cv-v3 installed effect in huggingface.co for debugging and trial. It also supports api for free installation.

w2v-bert-2.0-dhivehi-cv-v3 install url in huggingface.co:

https://huggingface.co/Serialtechlab/w2v-bert-2.0-dhivehi-cv-v3

Url of w2v-bert-2.0-dhivehi-cv-v3

w2v-bert-2.0-dhivehi-cv-v3 huggingface.co Url

Provider of w2v-bert-2.0-dhivehi-cv-v3 huggingface.co

Serialtechlab
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