Whisper Small Ablation Add NLD 80
This model is a fine-tuned version of openai/whisper-small on the fleurs dataset. It achieves the following results on the evaluation set: Loss: 0.4274 Wer: 17.0206
Fuente del modelo
- Tipo
- Text model
- Tamaño del archivo
- 922 MB
- Modelo base
- openai/whisper-small
- Versión
- vmodel
- Actualizado
- 2 oct 2026
- Publicador
- @octava
- Descargas
- 10
- Fuente
- Hugging Face
Descripción de la fuente
whisper-small-ablation-add-NLD-80
This model is a fine-tuned version of openai/whisper-small on the fleurs dataset. It achieves the following results on the evaluation set:
- Loss: 0.4274
- Wer: 17.0206
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: 32
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 1000
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.3531 | 0.4673 | 200 | 0.4262 | 18.9012 |
| 0.2799 | 0.9346 | 400 | 0.4623 | 18.4440 |
| 0.1829 | 1.4019 | 600 | 0.4345 | 18.7094 |
| 0.1841 | 1.8692 | 800 | 0.4215 | 17.1976 |
| 0.091 | 2.3364 | 1000 | 0.4274 | 17.0206 |
Framework versions
- Transformers 4.45.0
- Pytorch 2.11.0+cu130
- Datasets 3.0.1
- Tokenizers 0.20.0
Fuentes
1 fuente
Fuentes
1 fuenteVerificado 2 oct
Artefactos del modelo
1 artefacto
Artefactos del modelo
1 artefactolast-checkpoint/model.safetensors
safetensors · 922 MB · SHA-256 698f490de9f0…c37f · Hugging Face
DescargarExtractos de fuentes
3 extractos
Extractos de fuentes
3 extractos--- base_model: openai/whisper-small datasets: - fleurs library_name: transformers license: apache-2.0 metrics: - wer tags: - generated_from_trainer model-index: - name: whisper-small-ablation-add-NLD-80 results: - task: type: automatic-speech-recognition name: Automatic Speech Recognition dataset: name: fleurs type: fleurs config: id_id split: None args: id_id metrics: - type: wer value: 17.020648967551622 name: Wer --- <!-- 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-small-ablation-add-NLD-80 This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the fleurs dataset. It achieves the following results on the evaluation set: - Loss: 0.4274 - Wer: 17.0206 ## 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: 32 - eval_batch_size: 16 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 500 - training_steps: 1000 ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:------:|:----:|:---------------:|:-------:| | 0.3531 | 0.4673 | 200 | 0.4262 | 18.9012 | | 0.2799 | 0.9346 | 400 | 0.4623 | 18.4440 | | 0.1829 | 1.4019 | 600 | 0.4345 | 18.7094 | | 0.1841 | 1.8692 | 800 | 0.4215 | 17.1976 | | 0.091 | 2.3364 | 1000 | 0.4274 | 17.0206 | ### Framework versions - Transformers 4.45.0 - Pytorch 2.11.0+cu130 - Datasets 3.0.1 - Tokenizers 0.20.0
Source context: 10 downloads · 0 likes · Pipeline automatic-speech-recognition · Library transformers · Repo octava/whisper-small-ablation-add-NLD-80
Source context: 1 downloads · 0 likes · Pipeline automatic-speech-recognition · Library transformers · Repo octava/whisper-small-ablation-add-NLD-80
