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# STT_Model_17

This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1172
- Wer: 0.1190

## 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: 0.0001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 50

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 4.1934        | 2.1   | 500   | 3.7998          | 0.9999 |
| 1.14          | 4.2   | 1000  | 0.4083          | 0.3740 |
| 0.2217        | 6.3   | 1500  | 0.2515          | 0.2184 |
| 0.1276        | 8.4   | 2000  | 0.1623          | 0.1803 |
| 0.0914        | 10.5  | 2500  | 0.1586          | 0.1672 |
| 0.0731        | 12.61 | 3000  | 0.1648          | 0.1583 |
| 0.0572        | 14.71 | 3500  | 0.4059          | 0.1534 |
| 0.054         | 16.81 | 4000  | 0.1694          | 0.1391 |
| 0.043         | 18.91 | 4500  | 0.1390          | 0.1439 |
| 0.035         | 21.01 | 5000  | 0.1210          | 0.1362 |
| 0.0317        | 23.11 | 5500  | 0.1389          | 0.1285 |
| 0.031         | 25.21 | 6000  | 0.1340          | 0.1316 |
| 0.0266        | 27.31 | 6500  | 0.1312          | 0.1280 |
| 0.0209        | 29.41 | 7000  | 0.1484          | 0.1256 |
| 0.0184        | 31.51 | 7500  | 0.1345          | 0.1289 |
| 0.0201        | 33.61 | 8000  | 0.1350          | 0.1248 |
| 0.026         | 35.71 | 8500  | 0.1226          | 0.1235 |
| 0.016         | 37.82 | 9000  | 0.1235          | 0.1232 |
| 0.0115        | 39.92 | 9500  | 0.1223          | 0.1216 |
| 0.013         | 42.02 | 10000 | 0.1314          | 0.1206 |
| 0.0225        | 44.12 | 10500 | 0.1158          | 0.1211 |
| 0.011         | 46.22 | 11000 | 0.1181          | 0.1203 |
| 0.0106        | 48.32 | 11500 | 0.1172          | 0.1190 |


### Framework versions

- Transformers 4.27.3
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["wer"], "model-index": [{"name": "STT_Model_17", "results": []}]}
transformers pytorch tensorboard wav2vec2 automatic-speech-recognition generated_from_trainer license:apache-2.0 endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #generated_from_trainer #license-apache-2.0 #endpoints_compatible #region-us 

STT\_Model\_17
==============


This model is a fine-tuned version of facebook/wav2vec2-base on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 0.1172
* Wer: 0.1190


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: 0.0001
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 1000
* num\_epochs: 50


### Training results



### Framework versions


* Transformers 4.27.3
* Pytorch 1.13.1+cu116
* Datasets 2.10.1
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0001
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 1000
* num\_epochs: 50 ### Training results ### Framework versions


* Transformers 4.27.3
* Pytorch 1.13.1+cu116
* Datasets 2.10.1
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #wav2vec2 #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: 0.0001
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 1000
* num\_epochs: 50 ### Training results ### Framework versions


* Transformers 4.27.3
* Pytorch 1.13.1+cu116
* Datasets 2.10.1
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #wav2vec2 #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: 0.0001
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 1000
* num\_epochs: 50### Training results### Framework versions


* Transformers 4.27.3
* Pytorch 1.13.1+cu116
* Datasets 2.10.1
* Tokenizers 0.13.2