Whisper Small Finetuned Iwslt Welsh
This model is a fine-tuned version of openai/whisper-small on the covost2 dataset. It achieves the following results on the evaluation set: Loss: 3.7340 Wer: 82.1085 Bleu: 14.0988 Chrf++: 33.5907 Comet: 0.5541
Model source
- Kind
- Text model
- File size
- 922 MB
- Base model
- openai/whisper-small
- Version
- vmodel
- Updated
- Sep 22, 2026
- Downloads
- 22
- Source
- Hugging Face
Source description
whisper-small-finetuned-iwslt-welsh
This model is a fine-tuned version of openai/whisper-small on the covost2 dataset. It achieves the following results on the evaluation set:
- Loss: 3.7340
- Wer: 82.1085
- Bleu: 14.0988
- Chrf++: 33.5907
- Comet: 0.5541
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: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH 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: 1000
- training_steps: 5000
- mixed_precision_training: Native AMP
- label_smoothing_factor: 0.1
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Bleu | Chrf++ | Comet |
|---|---|---|---|---|---|---|---|
| 1.6851 | 16.0256 | 1250 | 3.2626 | 89.7478 | 11.2753 | 31.8587 | 0.5606 |
| 1.4611 | 32.0513 | 2500 | 3.4611 | 82.4896 | 14.0591 | 34.1147 | 0.5704 |
| 1.4471 | 48.0769 | 3750 | 3.6301 | 81.8000 | 14.0228 | 33.4928 | 0.5625 |
| 1.4415 | 64.1026 | 5000 | 3.7340 | 82.1085 | 14.0988 | 33.5907 | 0.5541 |
Framework versions
- Transformers 4.52.0
- Pytorch 2.11.0+cu128
- Datasets 2.21.0
- Tokenizers 0.21.4
Sources
1 source
Sources
1 sourceVerified Sep 22
Model artifacts
1 artifact
Model artifacts
1 artifactlast-checkpoint/model.safetensors
safetensors · 922 MB · SHA-256 44b1df0caed6…1d42 · Hugging Face
DownloadSource excerpts
2 excerpts
Source excerpts
2 excerpts--- library_name: transformers license: apache-2.0 base_model: openai/whisper-small tags: - generated_from_trainer datasets: - covost2 metrics: - wer - bleu model-index: - name: whisper-small-finetuned-iwslt-welsh results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: covost2 type: covost2 config: cy_en split: validation args: cy_en metrics: - name: Wer type: wer value: 82.10851025222283 - name: Bleu type: bleu value: 14.098824712552057 --- <!-- 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-finetuned-iwslt-welsh This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the covost2 dataset. It achieves the following results on the evaluation set: - Loss: 3.7340 - Wer: 82.1085 - Bleu: 14.0988 - Chrf++: 33.5907 - Comet: 0.5541 ## 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: 16 - eval_batch_size: 8 - seed: 42 - optimizer: Use OptimizerNames.ADAMW_TORCH 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: 1000 - training_steps: 5000 - mixed_precision_training: Native AMP - label_smoothing_factor: 0.1 ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | Bleu | Chrf++ | Comet | |:-------------:|:-------:|:----:|:---------------:|:-------:|:-------:|:-------:|:------:| | 1.6851 | 16.0256 | 1250 | 3.2626 | 89.7478 | 11.2753 | 31.8587 | 0.5606 | | 1.4611 | 32.0513 | 2500 | 3.4611 | 82.4896 | 14.0591 | 34.1147 | 0.5704 | | 1.4471 | 48.0769 | 3750 | 3.6301 | 81.8000 | 14.0228 | 33.4928 | 0.5625 | | 1.4415 | 64.1026 | 5000 | 3.7340 | 82.1085 | 14.0988 | 33.5907 | 0.5541 | ### Framework versions - Transformers 4.52.0 - Pytorch 2.11.0+cu128 - Datasets 2.21.0 - Tokenizers 0.21.4
Source context: 22 downloads · 0 likes · Pipeline automatic-speech-recognition · Library transformers · Repo jjnhuang/whisper-small-finetuned-iwslt-welsh
