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# Project_NLP

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: 0.5324
- Wer: 0.3355

## 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: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 3.5697        | 1.0   | 500   | 2.1035          | 0.9979 |
| 0.8932        | 2.01  | 1000  | 0.5649          | 0.5621 |
| 0.4363        | 3.01  | 1500  | 0.4326          | 0.4612 |
| 0.3035        | 4.02  | 2000  | 0.4120          | 0.4191 |
| 0.2343        | 5.02  | 2500  | 0.4199          | 0.3985 |
| 0.1921        | 6.02  | 3000  | 0.4380          | 0.4043 |
| 0.1549        | 7.03  | 3500  | 0.4456          | 0.3925 |
| 0.1385        | 8.03  | 4000  | 0.4264          | 0.3871 |
| 0.1217        | 9.04  | 4500  | 0.4744          | 0.3774 |
| 0.1041        | 10.04 | 5000  | 0.4498          | 0.3745 |
| 0.0968        | 11.04 | 5500  | 0.4716          | 0.3628 |
| 0.0893        | 12.05 | 6000  | 0.4680          | 0.3764 |
| 0.078         | 13.05 | 6500  | 0.5100          | 0.3623 |
| 0.0704        | 14.06 | 7000  | 0.4893          | 0.3552 |
| 0.0659        | 15.06 | 7500  | 0.4956          | 0.3565 |
| 0.0578        | 16.06 | 8000  | 0.5450          | 0.3595 |
| 0.0563        | 17.07 | 8500  | 0.4891          | 0.3614 |
| 0.0557        | 18.07 | 9000  | 0.5307          | 0.3548 |
| 0.0447        | 19.08 | 9500  | 0.4923          | 0.3493 |
| 0.0456        | 20.08 | 10000 | 0.5156          | 0.3479 |
| 0.0407        | 21.08 | 10500 | 0.4979          | 0.3389 |
| 0.0354        | 22.09 | 11000 | 0.5549          | 0.3462 |
| 0.0322        | 23.09 | 11500 | 0.5601          | 0.3439 |
| 0.0342        | 24.1  | 12000 | 0.5131          | 0.3451 |
| 0.0276        | 25.1  | 12500 | 0.5206          | 0.3392 |
| 0.0245        | 26.1  | 13000 | 0.5337          | 0.3373 |
| 0.0226        | 27.11 | 13500 | 0.5311          | 0.3353 |
| 0.0229        | 28.11 | 14000 | 0.5375          | 0.3373 |
| 0.0225        | 29.12 | 14500 | 0.5324          | 0.3355 |


### Framework versions

- Transformers 4.17.0
- Pytorch 1.11.0+cu113
- Datasets 1.18.3
- Tokenizers 0.12.1

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "model-index": [{"name": "Project_NLP", "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 

Project\_NLP
============


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: 0.5324
* Wer: 0.3355


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: 30
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.17.0
* Pytorch 1.11.0+cu113
* Datasets 1.18.3
* Tokenizers 0.12.1



### 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: 30
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.17.0
* Pytorch 1.11.0+cu113
* Datasets 1.18.3
* Tokenizers 0.12.1
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: 30
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.17.0
* Pytorch 1.11.0+cu113
* Datasets 1.18.3
* Tokenizers 0.12.1
passage: 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: 30
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.17.0
* Pytorch 1.11.0+cu113
* Datasets 1.18.3
* Tokenizers 0.12.1