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# wav2vec2-large-TIMIT-IPA2

This model is a fine-tuned version of [facebook/wav2vec2-large](https://huggingface.co/facebook/wav2vec2-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1531
- Per: 0.0638

## 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: 64
- eval_batch_size: 16
- 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: 100
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Per    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 2.0846        | 6.85  | 500  | 0.1810          | 0.0991 |
| 0.1857        | 13.7  | 1000 | 0.1411          | 0.0691 |
| 0.0948        | 20.55 | 1500 | 0.1345          | 0.0666 |
| 0.0646        | 27.4  | 2000 | 0.1444          | 0.0673 |
| 0.0502        | 34.25 | 2500 | 0.1436          | 0.0628 |
| 0.0381        | 41.1  | 3000 | 0.1383          | 0.0637 |
| 0.0309        | 47.95 | 3500 | 0.1533          | 0.0638 |
| 0.0261        | 54.79 | 4000 | 0.1531          | 0.0638 |


### Framework versions

- Transformers 4.20.0
- Pytorch 1.12.1+cu113
- Datasets 2.6.2.dev0
- Tokenizers 0.12.1

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "model-index": [{"name": "wav2vec2-large-TIMIT-IPA2", "results": []}]}
transformers pytorch wav2vec2 automatic-speech-recognition generated_from_trainer license:apache-2.0 endpoints_compatible region:us
TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #generated_from_trainer #license-apache-2.0 #endpoints_compatible #region-us 

wav2vec2-large-TIMIT-IPA2
=========================


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


* Loss: 0.1531
* Per: 0.0638


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: 64
* eval\_batch\_size: 16
* 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: 100
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.20.0
* Pytorch 1.12.1+cu113
* Datasets 2.6.2.dev0
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0001
* train\_batch\_size: 64
* eval\_batch\_size: 16
* 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: 100
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.20.0
* Pytorch 1.12.1+cu113
* Datasets 2.6.2.dev0
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #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: 64
* eval\_batch\_size: 16
* 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: 100
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.20.0
* Pytorch 1.12.1+cu113
* Datasets 2.6.2.dev0
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #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: 64
* eval\_batch\_size: 16
* 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: 100
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.20.0
* Pytorch 1.12.1+cu113
* Datasets 2.6.2.dev0
* Tokenizers 0.12.1