metadata
language:
- cy
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
base_model: openai/whisper-large-v2
model-index:
- name: openai/whisper-large-v2-welsh
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: Common Voice 11.0
type: mozilla-foundation/common_voice_11_0
config: cy
split: test
args: cy
metrics:
- type: wer
value: 18.06085160470289
name: Wer
openai/whisper-large-v2-welsh
This model is a fine-tuned version of openai/whisper-large-v2 on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.2947
- Wer: 18.0609
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: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- 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: 50
- training_steps: 500
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.4438 | 0.2 | 100 | 0.4208 | 27.3594 |
| 0.3255 | 0.4 | 200 | 0.3633 | 23.6118 |
| 0.2856 | 0.6 | 300 | 0.3248 | 20.7023 |
| 0.1811 | 1.14 | 400 | 0.3011 | 18.5534 |
| 0.1404 | 1.34 | 500 | 0.2947 | 18.0609 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2