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---
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
- generated_from_trainer
datasets:
- DewiBrynJones/oscar-cy-tts
metrics:
- wer
model-index:
- name: whisper-large-v3-ft-tts-cy
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: DewiBrynJones/oscar-cy-tts default
type: DewiBrynJones/oscar-cy-tts
args: default
metrics:
- name: Wer
type: wer
value: 0.1561639017527405
---
<!-- 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-large-v3-ft-tts-cy
This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the DewiBrynJones/oscar-cy-tts default dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2108
- Wer: 0.1562
## 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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 5000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 0.3429 | 0.2627 | 1000 | 0.3296 | 0.2300 |
| 0.2636 | 0.5255 | 2000 | 0.2615 | 0.1926 |
| 0.2316 | 0.7882 | 3000 | 0.2340 | 0.1798 |
| 0.1779 | 1.0510 | 4000 | 0.2179 | 0.1624 |
| 0.1626 | 1.3137 | 5000 | 0.2108 | 0.1562 |
### Framework versions
- Transformers 4.44.0
- Pytorch 2.4.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
|