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Whisper Mdd Plan3

This model is a fine-tuned version of openai/whisper-large-v3-turbo on an unknown dataset. It achieves the following results on the evaluation set: Loss: 0.3860 Accuracy: 0.9230 Precision: 0.2060 Recall: 0.2502 F1:...

Fontehuggingface.co/Nieves0112/whisper_mdd_plan3/tree/8abfead6180ccdcd2e2312a33dccd71afc535ee9
TipoText modelModelo baseopenai/whisper-large-v3-turboVersãomodelPublicador@Nieves0112Cnota

Fonte do modelo

Tipo
Text model
Tamanho do arquivo
1,53 GB
Modelo base
openai/whisper-large-v3-turbo
Versão
vmodel
Atualizado
2 de out. de 2026
Publicador
@Nieves0112
Downloads
0
Fonte
Hugging Face

Descrição da fonte

whisper_mdd_plan3

This model is a fine-tuned version of openai/whisper-large-v3-turbo on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3860
  • Accuracy: 0.9230
  • Precision: 0.2060
  • Recall: 0.2502
  • F1: 0.2260

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: 8
  • eval_batch_size: 8
  • seed: 42
  • 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: 0.1
  • num_epochs: 10

Training results

Training LossEpochStepValidation LossAccuracyPrecisionRecallF1
0.67241.04340.69980.955100.00
0.70182.08680.54700.955100.00
0.64393.013020.44720.955100.00
0.66964.017360.42610.955100.00
0.69885.021700.48110.80770.10640.44360.1716
0.56496.026040.40440.93190.18880.15660.1712
0.59057.030380.38880.94360.21760.09880.1359
0.57988.034720.38530.93130.21050.19240.2010
0.55709.039060.41530.90360.17610.31190.2251
0.480910.043400.38600.92300.20600.25020.2260

Framework versions

  • Transformers 5.8.0
  • Pytorch 2.8.0+cu128
  • Datasets 4.8.5
  • Tokenizers 0.22.2

Fontes

1 fonte
Hugging FacePrimárioVersão 8abfead6180ccdcd2e2312a33dccd71afc535ee9
huggingface.co/Nieves0112/whisper_mdd_plan3/tree/8abfead6180ccdcd2e2312a33dccd71afc535ee9

Verificado 2 de out.

Artefatos de modelo

1 artefato

model.safetensors

safetensors · 1,53 GB · SHA-256 628c8df424d4…901f · Hugging Face

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Trechos de fonte

3 trechos
Readme11 de jul.huggingface.co/Nieves0112/whisper_mdd_plan3

--- library_name: transformers license: mit base_model: openai/whisper-large-v3-turbo tags: - generated_from_trainer metrics: - accuracy - precision - recall - f1 model-index: - name: whisper_mdd_plan3 results: [] --- <!-- 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. --> # whisper_mdd_plan3 This model is a fine-tuned version of [openai/whisper-large-v3-turbo](https://huggingface.co/openai/whisper-large-v3-turbo) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.3860 - Accuracy: 0.9230 - Precision: 0.2060 - Recall: 0.2502 - F1: 0.2260 ## 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: 8 - eval_batch_size: 8 - seed: 42 - 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: 0.1 - num_epochs: 10 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| | 0.6724 | 1.0 | 434 | 0.6998 | 0.9551 | 0 | 0.0 | 0 | | 0.7018 | 2.0 | 868 | 0.5470 | 0.9551 | 0 | 0.0 | 0 | | 0.6439 | 3.0 | 1302 | 0.4472 | 0.9551 | 0 | 0.0 | 0 | | 0.6696 | 4.0 | 1736 | 0.4261 | 0.9551 | 0 | 0.0 | 0 | | 0.6988 | 5.0 | 2170 | 0.4811 | 0.8077 | 0.1064 | 0.4436 | 0.1716 | | 0.5649 | 6.0 | 2604 | 0.4044 | 0.9319 | 0.1888 | 0.1566 | 0.1712 | | 0.5905 | 7.0 | 3038 | 0.3888 | 0.9436 | 0.2176 | 0.0988 | 0.1359 | | 0.5798 | 8.0 | 3472 | 0.3853 | 0.9313 | 0.2105 | 0.1924 | 0.2010 | | 0.5570 | 9.0 | 3906 | 0.4153 | 0.9036 | 0.1761 | 0.3119 | 0.2251 | | 0.4809 | 10.0 | 4340 | 0.3860 | 0.9230 | 0.2060 | 0.2502 | 0.2260 | ### Framework versions - Transformers 5.8.0 - Pytorch 2.8.0+cu128 - Datasets 4.8.5 - Tokenizers 0.22.2

Note11 de jul.huggingface.co/Nieves0112/whisper_mdd_plan3

Source context: 0 downloads · 1 likes · Library transformers · Repo Nieves0112/whisper_mdd_plan3

Note17 de mai.huggingface.co/api/models/Nieves0112/whisper_mdd_plan3

Source context: 0 downloads · 0 likes · Library transformers · Repo Nieves0112/whisper_mdd_plan3