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---
license: apache-2.0
tags:
- generated_from_trainer
- whisper-event
datasets:
- vumichien/preprocessed_jsut_jsss_css10_common_voice_11
metrics:
- wer
- cer
base_model: openai/whisper-large-v2
model-index:
- name: openai/whisper-large-v2
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: mozilla-foundation/common_voice_11_0 ja
type: mozilla-foundation/common_voice_11_0
config: ja
split: test
args: ja
metrics:
- type: wer
value: 7.6453
name: Wer
- type: cer
value: 4.7187
name: Cer
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: google/fleurs
type: google/fleurs
config: ja_jp
split: test
metrics:
- type: wer
value: 11.69
name: WER
- type: cer
value: 7.12
name: CER
---
<!-- 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. -->
# openai/whisper-large-v2
This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the vumichien/preprocessed_jsut_jsss_css10_common_voice_11 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2284
- Wer: 7.6453
- Cer: 4.7187
## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 10000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:------:|
| 0.1912 | 0.55 | 1000 | 0.1828 | 11.2314 | 7.0357 |
| 0.1329 | 1.1 | 2000 | 0.1618 | 9.4172 | 5.9028 |
| 0.0912 | 1.65 | 3000 | 0.1616 | 8.9257 | 5.4711 |
| 0.0576 | 2.2 | 4000 | 0.1664 | 8.5861 | 5.3055 |
| 0.0449 | 2.74 | 5000 | 0.1642 | 8.4510 | 5.2930 |
| 0.02 | 3.29 | 6000 | 0.1799 | 8.1537 | 5.0354 |
| 0.019 | 3.84 | 7000 | 0.1801 | 8.125 | 5.0827 |
| 0.0067 | 4.39 | 8000 | 0.2003 | 7.8412 | 4.8133 |
| 0.006 | 4.94 | 9000 | 0.2071 | 7.5811 | 4.7023 |
| 0.0022 | 5.49 | 10000 | 0.2284 | 7.6453 | 4.7187 |
### Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2
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