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# whisper-tiny-v2-ta_tf32_adamBetas_2

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: 0.3491
- Wer: 43.1477

## 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: 1.5e-05
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.98) and epsilon=1e-06
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 4000

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.6508        | 0.11  | 300  | 0.5656          | 54.3341 |
| 0.4612        | 0.21  | 600  | 0.4615          | 50.4600 |
| 0.408         | 0.32  | 900  | 0.4190          | 47.4576 |
| 0.3692        | 0.42  | 1200 | 0.4001          | 52.0581 |
| 0.3486        | 0.53  | 1500 | 0.3858          | 51.2349 |
| 0.3245        | 0.63  | 1800 | 0.3791          | 45.6174 |
| 0.3274        | 0.74  | 2100 | 0.3632          | 42.1792 |
| 0.2985        | 0.84  | 2400 | 0.3566          | 43.7288 |
| 0.2849        | 0.95  | 2700 | 0.3548          | 43.3898 |
| 0.2717        | 1.05  | 3000 | 0.3491          | 43.1477 |


### Framework versions

- Transformers 4.28.0.dev0
- Pytorch 1.12.1
- Datasets 2.11.0
- Tokenizers 0.13.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["wer"], "model-index": [{"name": "whisper-tiny-v2-ta_tf32_adamBetas_2", "results": []}]}
transformers pytorch tensorboard whisper automatic-speech-recognition generated_from_trainer license:apache-2.0 endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #whisper #automatic-speech-recognition #generated_from_trainer #license-apache-2.0 #endpoints_compatible #region-us 

whisper-tiny-v2-ta\_tf32\_adamBetas\_2
======================================


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: 0.3491
* Wer: 43.1477


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: 1.5e-05
* train\_batch\_size: 4
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 8
* total\_train\_batch\_size: 32
* optimizer: Adam with betas=(0.9,0.98) and epsilon=1e-06
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 500
* training\_steps: 4000


### Training results



### Framework versions


* Transformers 4.28.0.dev0
* Pytorch 1.12.1
* Datasets 2.11.0
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1.5e-05
* train\_batch\_size: 4
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 8
* total\_train\_batch\_size: 32
* optimizer: Adam with betas=(0.9,0.98) and epsilon=1e-06
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 500
* training\_steps: 4000 ### Training results ### Framework versions


* Transformers 4.28.0.dev0
* Pytorch 1.12.1
* Datasets 2.11.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #whisper #automatic-speech-recognition #generated_from_trainer #license-apache-2.0 #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1.5e-05
* train\_batch\_size: 4
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 8
* total\_train\_batch\_size: 32
* optimizer: Adam with betas=(0.9,0.98) and epsilon=1e-06
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 500
* training\_steps: 4000 ### Training results ### Framework versions


* Transformers 4.28.0.dev0
* Pytorch 1.12.1
* Datasets 2.11.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #whisper #automatic-speech-recognition #generated_from_trainer #license-apache-2.0 #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1.5e-05
* train\_batch\_size: 4
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 8
* total\_train\_batch\_size: 32
* optimizer: Adam with betas=(0.9,0.98) and epsilon=1e-06
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 500
* training\_steps: 4000### Training results### Framework versions


* Transformers 4.28.0.dev0
* Pytorch 1.12.1
* Datasets 2.11.0
* Tokenizers 0.13.3