Wav2vec Base Finetuned TESS
This model is a fine-tuned version of facebook/wav2vec2-base on an unknown dataset. It achieves the following results on the evaluation set: Loss: 0.3143 Accuracy: 1.0
Source du modèle
- Type
- Other
- Taille du fichier
- 361 MB
- Modèle de base
- facebook/wav2vec2-base
- Version
- vRevision 68fb8b9
- Mis à jour
- 25 oct. 2026
- Téléchargements
- 3
- Source
- Hugging Face
Description de la source
wav2vec-base-finetuned-TESS
This model is a fine-tuned version of facebook/wav2vec2-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3143
- Accuracy: 1.0
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: 3e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- 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: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 4.3985 | 1.0 | 140 | 1.1045 | 0.9964 |
| 1.1345 | 2.0 | 280 | 0.3143 | 1.0 |
| 0.3729 | 3.0 | 420 | 0.1179 | 1.0 |
| 0.1744 | 4.0 | 560 | 0.0658 | 1.0 |
| 0.1340 | 5.0 | 700 | 0.0558 | 1.0 |
Framework versions
- Transformers 5.0.0
- Pytorch 2.10.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2
Sources
1 source
Sources
1 sourceVérifié 25 oct.
Artefacts du modèle
1 artefact
Artefacts du modèle
1 artefactExtraits de sources
3 extraits
Extraits de sources
3 extraits--- library_name: transformers license: apache-2.0 base_model: facebook/wav2vec2-base tags: - generated_from_trainer metrics: - accuracy model-index: - name: wav2vec-base-finetuned-TESS 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. --> # wav2vec-base-finetuned-TESS This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.3143 - Accuracy: 1.0 ## 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: 3e-05 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - gradient_accumulation_steps: 2 - total_train_batch_size: 16 - 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: 5 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 4.3985 | 1.0 | 140 | 1.1045 | 0.9964 | | 1.1345 | 2.0 | 280 | 0.3143 | 1.0 | | 0.3729 | 3.0 | 420 | 0.1179 | 1.0 | | 0.1744 | 4.0 | 560 | 0.0658 | 1.0 | | 0.1340 | 5.0 | 700 | 0.0558 | 1.0 | ### Framework versions - Transformers 5.0.0 - Pytorch 2.10.0+cu128 - Datasets 4.0.0 - Tokenizers 0.22.2
Source context: 3 downloads · 0 likes · Pipeline audio-classification · Library transformers · Repo VasilisAsim/wav2vec-base-finetuned-TESS
Source context: 6 downloads · 0 likes · Pipeline audio-classification · Library transformers · Repo VasilisAsim/wav2vec-base-finetuned-TESS
