Waxal Multilingual Small
This model is a fine-tuned version of openai/whisper-small on the None dataset. It achieves the following results on the evaluation set: Loss: 0.8138 Wer: 59.8955
Fonte do modelo
- Tipo
- Text model
- Tamanho do arquivo
- 922 MB
- Modelo base
- openai/whisper-small
- Versão
- vmodel
- Atualizado
- 26 de out. de 2026
- Downloads
- 4
- Fonte
- Hugging Face
Descrição da fonte
waxal-multilingual-small
This model is a fine-tuned version of openai/whisper-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.8138
- Wer: 59.8955
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: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- 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: 100
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 6.5323 | 1.4192 | 200 | 0.9384 | 69.9910 |
| 4.6984 | 2.8384 | 400 | 0.8138 | 59.8955 |
| 3.2969 | 4.2558 | 600 | 0.8019 | 60.4374 |
Framework versions
- Transformers 5.0.0
- Pytorch 2.10.0+cu128
- Datasets 5.0.0
- Tokenizers 0.22.2
Fontes
1 fonte
Fontes
1 fonteVerificado 26 de out.
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Artefatos de modelo
2 artefatos
Artefatos de modelo
2 artefatosfinal_model/model.safetensors
safetensors · 922 MB · SHA-256 47cd0ff0e253…425c · Hugging Face
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Trechos de fonte
3 trechos--- library_name: transformers license: apache-2.0 base_model: openai/whisper-small tags: - generated_from_trainer metrics: - wer model-index: - name: waxal-multilingual-small 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. --> # waxal-multilingual-small This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.8138 - Wer: 59.8955 ## 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: 1e-05 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - gradient_accumulation_steps: 4 - 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: 100 - num_epochs: 5 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:------:|:----:|:---------------:|:-------:| | 6.5323 | 1.4192 | 200 | 0.9384 | 69.9910 | | 4.6984 | 2.8384 | 400 | 0.8138 | 59.8955 | | 3.2969 | 4.2558 | 600 | 0.8019 | 60.4374 | ### Framework versions - Transformers 5.0.0 - Pytorch 2.10.0+cu128 - Datasets 5.0.0 - Tokenizers 0.22.2
Source context: 4 downloads · 0 likes · Pipeline automatic-speech-recognition · Library transformers · Repo sandilecwili007/waxal-multilingual-small
Source context: 54 downloads · 0 likes · Pipeline automatic-speech-recognition · Library transformers · Repo sandilecwili007/waxal-multilingual-small
