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# Whisper large-v2 nan-tw only char

This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the mozilla-foundation/common_voice_11_0 nan-tw dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0351
- Wer: 45.3740
- Cer: 45.4573

## 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: 2
- eval_batch_size: 2
- seed: 42
- 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     | Cer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|
| 0.6011        | 1.04  | 1000 | 1.1100          | 55.0229 | 55.2068 |
| 0.1773        | 2.08  | 2000 | 1.2055          | 58.6565 | 58.7685 |
| 0.015         | 3.13  | 3000 | 1.0932          | 48.6412 | 48.8077 |
| 0.0131        | 5.01  | 4000 | 1.0531          | 45.7099 | 45.8497 |
| 0.0001        | 6.05  | 5000 | 1.0351          | 45.3740 | 45.4573 |


### Framework versions

- Transformers 4.27.0.dev0
- Pytorch 1.13.1+cu117
- Datasets 2.8.0
- Tokenizers 0.13.2

{"language": ["zh"], "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": "Whisper large-v2 nan-tw only char", "results": [{"task": {"type": "automatic-speech-recognition", "name": "Automatic Speech Recognition"}, "dataset": {"name": "mozilla-foundation/common_voice_11_0 nan-tw", "type": "mozilla-foundation/common_voice_11_0", "config": "nan-tw", "split": "test", "args": "nan-tw"}, "metrics": [{"type": "wer", "value": 45.37404580152672, "name": "Wer"}]}]}]}
transformers pytorch tensorboard safetensors whisper automatic-speech-recognition whisper-event generated_from_trainer zh dataset:mozilla-foundation/common_voice_11_0 base_model:openai/whisper-large-v2 license:apache-2.0 model-index endpoints_compatible has_space region:us
TAGS
#transformers #pytorch #tensorboard #safetensors #whisper #automatic-speech-recognition #whisper-event #generated_from_trainer #zh #dataset-mozilla-foundation/common_voice_11_0 #base_model-openai/whisper-large-v2 #license-apache-2.0 #model-index #endpoints_compatible #has_space #region-us 

Whisper large-v2 nan-tw only char
=================================


This model is a fine-tuned version of openai/whisper-large-v2 on the mozilla-foundation/common\_voice\_11\_0 nan-tw dataset.
It achieves the following results on the evaluation set:


* Loss: 1.0351
* Wer: 45.3740
* Cer: 45.4573


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: 2
* eval\_batch\_size: 2
* seed: 42
* 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



### Framework versions


* Transformers 4.27.0.dev0
* Pytorch 1.13.1+cu117
* Datasets 2.8.0
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1e-05
* train\_batch\_size: 2
* eval\_batch\_size: 2
* seed: 42
* 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 ### Framework versions


* Transformers 4.27.0.dev0
* Pytorch 1.13.1+cu117
* Datasets 2.8.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #safetensors #whisper #automatic-speech-recognition #whisper-event #generated_from_trainer #zh #dataset-mozilla-foundation/common_voice_11_0 #base_model-openai/whisper-large-v2 #license-apache-2.0 #model-index #endpoints_compatible #has_space #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1e-05
* train\_batch\_size: 2
* eval\_batch\_size: 2
* seed: 42
* 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 ### Framework versions


* Transformers 4.27.0.dev0
* Pytorch 1.13.1+cu117
* Datasets 2.8.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #safetensors #whisper #automatic-speech-recognition #whisper-event #generated_from_trainer #zh #dataset-mozilla-foundation/common_voice_11_0 #base_model-openai/whisper-large-v2 #license-apache-2.0 #model-index #endpoints_compatible #has_space #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1e-05
* train\_batch\_size: 2
* eval\_batch\_size: 2
* seed: 42
* 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### Framework versions


* Transformers 4.27.0.dev0
* Pytorch 1.13.1+cu117
* Datasets 2.8.0
* Tokenizers 0.13.2