|
--- |
|
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: 0.10755268881722042 |
|
--- |
|
|
|
<!-- 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: 0.1365 |
|
- Wer: 0.1076 |
|
|
|
## 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 | |
|
|:-------------:|:------:|:----:|:---------------:|:------:| |
|
| 0.2469 | 0.3232 | 1000 | 0.2313 | 0.1733 | |
|
| 0.1578 | 0.6464 | 2000 | 0.1785 | 0.1373 | |
|
| 0.1491 | 0.9696 | 3000 | 0.1531 | 0.1213 | |
|
| 0.099 | 1.2928 | 4000 | 0.1434 | 0.1129 | |
|
| 0.0874 | 1.6160 | 5000 | 0.1365 | 0.1076 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.44.0 |
|
- Pytorch 2.4.0+cu121 |
|
- Datasets 2.20.0 |
|
- Tokenizers 0.19.1 |
|
|
