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# NLP_Project

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: 0.5308
- Wer: 0.3428

## 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    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 3.5939        | 1.0   | 500   | 2.1356          | 1.0014 |
| 0.9126        | 2.01  | 1000  | 0.5469          | 0.5354 |
| 0.4491        | 3.01  | 1500  | 0.4636          | 0.4503 |
| 0.3008        | 4.02  | 2000  | 0.4269          | 0.4330 |
| 0.2229        | 5.02  | 2500  | 0.4164          | 0.4073 |
| 0.188         | 6.02  | 3000  | 0.4717          | 0.4107 |
| 0.1739        | 7.03  | 3500  | 0.4306          | 0.4031 |
| 0.159         | 8.03  | 4000  | 0.4394          | 0.3993 |
| 0.1342        | 9.04  | 4500  | 0.4462          | 0.3904 |
| 0.1093        | 10.04 | 5000  | 0.4387          | 0.3759 |
| 0.1005        | 11.04 | 5500  | 0.5033          | 0.3847 |
| 0.0857        | 12.05 | 6000  | 0.4805          | 0.3876 |
| 0.0779        | 13.05 | 6500  | 0.5269          | 0.3810 |
| 0.072         | 14.06 | 7000  | 0.5109          | 0.3710 |
| 0.0641        | 15.06 | 7500  | 0.4865          | 0.3638 |
| 0.0584        | 16.06 | 8000  | 0.5041          | 0.3646 |
| 0.0552        | 17.07 | 8500  | 0.4987          | 0.3537 |
| 0.0535        | 18.07 | 9000  | 0.4947          | 0.3586 |
| 0.0475        | 19.08 | 9500  | 0.5237          | 0.3647 |
| 0.042         | 20.08 | 10000 | 0.5338          | 0.3561 |
| 0.0416        | 21.08 | 10500 | 0.5068          | 0.3483 |
| 0.0358        | 22.09 | 11000 | 0.5126          | 0.3532 |
| 0.0334        | 23.09 | 11500 | 0.5213          | 0.3536 |
| 0.0331        | 24.1  | 12000 | 0.5378          | 0.3496 |
| 0.03          | 25.1  | 12500 | 0.5167          | 0.3470 |
| 0.0254        | 26.1  | 13000 | 0.5245          | 0.3418 |
| 0.0233        | 27.11 | 13500 | 0.5393          | 0.3456 |
| 0.0232        | 28.11 | 14000 | 0.5279          | 0.3425 |
| 0.022         | 29.12 | 14500 | 0.5308          | 0.3428 |


### 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": "NLP_Project", "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 

NLP\_Project
============


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: 0.5308
* Wer: 0.3428


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