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# whisper-tiny-full-data-v1

This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5167

## 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: 0.0015
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- distributed_type: tpu
- num_devices: 8
- total_train_batch_size: 256
- total_eval_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1024
- training_steps: 63840

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 1.5098        | 1.0   | 3192  | 1.8031          |
| 1.1616        | 2.0   | 6384  | 1.4578          |
| 1.0512        | 3.0   | 9576  | 1.3050          |
| 1.0219        | 4.0   | 12768 | 1.2848          |
| 0.9588        | 5.0   | 15960 | 1.2070          |
| 0.8933        | 6.0   | 19152 | 1.1487          |
| 0.8523        | 7.0   | 22344 | 1.0769          |
| 0.8058        | 8.0   | 25536 | 1.0350          |
| 0.7441        | 9.0   | 28728 | 0.9768          |
| 0.6941        | 10.0  | 31920 | 0.9111          |
| 0.6478        | 11.0  | 35112 | 0.8570          |
| 0.6015        | 12.0  | 38304 | 0.8058          |
| 0.5514        | 13.0  | 41496 | 0.7537          |
| 0.5175        | 14.0  | 44688 | 0.6989          |
| 0.4691        | 15.0  | 47880 | 0.6547          |
| 0.4343        | 16.0  | 51072 | 0.6162          |
| 0.4078        | 17.0  | 54264 | 0.5818          |
| 0.3788        | 18.0  | 57456 | 0.5503          |
| 0.3571        | 19.0  | 60648 | 0.5276          |
| 0.346         | 20.0  | 63840 | 0.5167          |


### Framework versions

- Transformers 4.29.2
- Pytorch 2.1.0a0+gitcc01568
- Datasets 2.12.0
- Tokenizers 0.13.3

{"license": "apache-2.0", "tags": ["whisper-event", "generated_from_trainer"], "model-index": [{"name": "whisper-tiny-full-data-v1", "results": []}]}
transformers pytorch whisper automatic-speech-recognition whisper-event generated_from_trainer license:apache-2.0 endpoints_compatible region:us
TAGS
#transformers #pytorch #whisper #automatic-speech-recognition #whisper-event #generated_from_trainer #license-apache-2.0 #endpoints_compatible #region-us 

whisper-tiny-full-data-v1
=========================


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


* Loss: 0.5167


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: 0.0015
* train\_batch\_size: 32
* eval\_batch\_size: 8
* seed: 42
* distributed\_type: tpu
* num\_devices: 8
* total\_train\_batch\_size: 256
* total\_eval\_batch\_size: 64
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 1024
* training\_steps: 63840


### Training results



### Framework versions


* Transformers 4.29.2
* Pytorch 2.1.0a0+gitcc01568
* Datasets 2.12.0
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0015
* train\_batch\_size: 32
* eval\_batch\_size: 8
* seed: 42
* distributed\_type: tpu
* num\_devices: 8
* total\_train\_batch\_size: 256
* total\_eval\_batch\_size: 64
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 1024
* training\_steps: 63840 ### Training results ### Framework versions


* Transformers 4.29.2
* Pytorch 2.1.0a0+gitcc01568
* Datasets 2.12.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #whisper #automatic-speech-recognition #whisper-event #generated_from_trainer #license-apache-2.0 #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0015
* train\_batch\_size: 32
* eval\_batch\_size: 8
* seed: 42
* distributed\_type: tpu
* num\_devices: 8
* total\_train\_batch\_size: 256
* total\_eval\_batch\_size: 64
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 1024
* training\_steps: 63840 ### Training results ### Framework versions


* Transformers 4.29.2
* Pytorch 2.1.0a0+gitcc01568
* Datasets 2.12.0
* Tokenizers 0.13.3