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---
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
- generated_from_trainer
datasets:
- DewiBrynJones/commonvoice_18_0_cy
metrics:
- wer
model-index:
- name: whisper-large-v3-ft-fz-cv-cy
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: DewiBrynJones/commonvoice_18_0_cy default
type: DewiBrynJones/commonvoice_18_0_cy
args: default
metrics:
- name: Wer
type: wer
value: 0.2715416119925246
---
<!-- 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-fz-cv-cy
This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the DewiBrynJones/commonvoice_18_0_cy default dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5067
- Wer: 0.2715
## 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 |
|:-------------:|:-------:|:----:|:---------------:|:------:|
| 0.1024 | 4.0161 | 1000 | 0.3592 | 0.2914 |
| 0.0052 | 8.0321 | 2000 | 0.4336 | 0.2667 |
| 0.0014 | 12.0482 | 3000 | 0.4721 | 0.2708 |
| 0.0006 | 16.0643 | 4000 | 0.4972 | 0.2700 |
| 0.0005 | 20.0803 | 5000 | 0.5067 | 0.2715 |
### Framework versions
- Transformers 4.44.0
- Pytorch 2.4.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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