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# 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 None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1902
- Wer: 10.0204

## 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: 32
- 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: 4000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.2223        | 0.12  | 500  | 0.2384          | 11.3393 |
| 0.2291        | 0.25  | 1000 | 0.2043          | 10.2326 |
| 0.1116        | 1.04  | 1500 | 0.1999          | 9.9402  |
| 0.1433        | 1.16  | 2000 | 0.1897          | 10.1128 |
| 0.0687        | 1.29  | 2500 | 0.1876          | 9.9270  |
| 0.067         | 2.07  | 3000 | 0.2089          | 10.6712 |
| 0.0819        | 2.2   | 3500 | 0.1962          | 10.3128 |
| 0.0587        | 2.32  | 4000 | 0.1902          | 10.0204 |


### Framework versions

- Transformers 4.27.0.dev0
- Pytorch 1.13.1+cu117
- Datasets 2.9.1.dev0
- Tokenizers 0.13.2

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["wer"], "model-index": [{"name": "openai/whisper-large-v2", "results": [{"task": {"type": "automatic-speech-recognition", "name": "Automatic Speech Recognition"}, "dataset": {"name": "rishabhjain16/infer_myst", "type": "rishabhjain16/infer_myst", "config": "en", "split": "test"}, "metrics": [{"type": "wer", "value": 12.37, "name": "WER"}]}, {"task": {"type": "automatic-speech-recognition", "name": "Automatic Speech Recognition"}, "dataset": {"name": "rishabhjain16/infer_pfs", "type": "rishabhjain16/infer_pfs", "config": "en", "split": "test"}, "metrics": [{"type": "wer", "value": 3.1, "name": "WER"}]}, {"task": {"type": "automatic-speech-recognition", "name": "Automatic Speech Recognition"}, "dataset": {"name": "rishabhjain16/infer_cmu", "type": "rishabhjain16/infer_cmu", "config": "en", "split": "test"}, "metrics": [{"type": "wer", "value": 1.86, "name": "WER"}]}, {"task": {"type": "automatic-speech-recognition", "name": "Automatic Speech Recognition"}, "dataset": {"name": "rishabhjain16/libritts_dev_clean", "type": "rishabhjain16/libritts_dev_clean", "config": "en", "split": "test"}, "metrics": [{"type": "wer", "value": 4.75, "name": "WER"}]}, {"task": {"type": "automatic-speech-recognition", "name": "Automatic Speech Recognition"}, "dataset": {"name": "rishabhjain16/infer_pf_swedish", "type": "rishabhjain16/infer_pf_swedish", "config": "en", "split": "test"}, "metrics": [{"type": "wer", "value": 43.43, "name": "WER"}]}, {"task": {"type": "automatic-speech-recognition", "name": "Automatic Speech Recognition"}, "dataset": {"name": "rishabhjain16/infer_pf_german", "type": "rishabhjain16/infer_pf_german", "config": "en", "split": "test"}, "metrics": [{"type": "wer", "value": 71.18, "name": "WER"}]}, {"task": {"type": "automatic-speech-recognition", "name": "Automatic Speech Recognition"}, "dataset": {"name": "rishabhjain16/infer_pf_italian", "type": "rishabhjain16/infer_pf_italian", "config": "en", "split": "test"}, "metrics": [{"type": "wer", "value": 56.29, "name": "WER"}]}, {"task": {"type": "automatic-speech-recognition", "name": "Automatic Speech Recognition"}, "dataset": {"name": "rishabhjain16/infer_so_chinese", "type": "rishabhjain16/infer_so_chinese", "config": "en", "split": "test"}, "metrics": [{"type": "wer", "value": 32.99, "name": "WER"}]}]}]}
transformers pytorch tensorboard whisper automatic-speech-recognition generated_from_trainer license:apache-2.0 model-index endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #whisper #automatic-speech-recognition #generated_from_trainer #license-apache-2.0 #model-index #endpoints_compatible #region-us 

openai/whisper-large-v2
=======================


This model is a fine-tuned version of openai/whisper-large-v2 on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 0.1902
* Wer: 10.0204


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: 32
* 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: 4000
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.27.0.dev0
* Pytorch 1.13.1+cu117
* Datasets 2.9.1.dev0
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1e-05
* train\_batch\_size: 16
* eval\_batch\_size: 32
* 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: 4000
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.27.0.dev0
* Pytorch 1.13.1+cu117
* Datasets 2.9.1.dev0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #whisper #automatic-speech-recognition #generated_from_trainer #license-apache-2.0 #model-index #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1e-05
* train\_batch\_size: 16
* eval\_batch\_size: 32
* 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: 4000
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.27.0.dev0
* Pytorch 1.13.1+cu117
* Datasets 2.9.1.dev0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #whisper #automatic-speech-recognition #generated_from_trainer #license-apache-2.0 #model-index #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1e-05
* train\_batch\_size: 16
* eval\_batch\_size: 32
* 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: 4000
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.27.0.dev0
* Pytorch 1.13.1+cu117
* Datasets 2.9.1.dev0
* Tokenizers 0.13.2