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---
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
- generated_from_trainer
datasets:
- DewiBrynJones/banc-trawsgrifiadau-bangor-clean
metrics:
- wer
model-index:
- name: whisper-large-v3-ft-btb-cy
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: DewiBrynJones/banc-trawsgrifiadau-bangor-clean default
type: DewiBrynJones/banc-trawsgrifiadau-bangor-clean
args: default
metrics:
- name: Wer
type: wer
value: 0.2817565771990433
---
<!-- 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-btb-cy
This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the DewiBrynJones/banc-trawsgrifiadau-bangor-clean default dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5500
- Wer: 0.2818
## 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 |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 0.3452 | 1.1390 | 1000 | 0.4484 | 0.3166 |
| 0.2029 | 2.2779 | 2000 | 0.4125 | 0.2898 |
| 0.1143 | 3.4169 | 3000 | 0.4329 | 0.2814 |
| 0.0515 | 4.5558 | 4000 | 0.4906 | 0.2832 |
| 0.0193 | 5.6948 | 5000 | 0.5500 | 0.2818 |
### Framework versions
- Transformers 4.44.0
- Pytorch 2.4.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
|