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# wav2vec2_xlsr50k_english_phoneme

This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on [the TIMIT dataset](https://catalog.ldc.upenn.edu/LDC93s1).
It achieves the following results on the evaluation set:
- Loss: 0.5783
- Cer: 0.1178

## 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: 0.0003
- train_batch_size: 32
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 50
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Cer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 4.8403        | 6.94  | 500  | 1.1345          | 0.4657 |
| 0.5795        | 13.88 | 1000 | 0.3579          | 0.1169 |
| 0.3567        | 20.83 | 1500 | 0.3866          | 0.1174 |
| 0.2717        | 27.77 | 2000 | 0.4219          | 0.1169 |
| 0.2135        | 34.72 | 2500 | 0.4861          | 0.1199 |
| 0.1664        | 41.66 | 3000 | 0.5490          | 0.1179 |
| 0.1375        | 48.61 | 3500 | 0.5783          | 0.1178 |


### Framework versions

- Transformers 4.22.0.dev0
- Pytorch 1.12.1
- Datasets 1.13.3
- Tokenizers 0.12.1

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "model-index": [{"name": "wav2vec2_xlsr50k_english_phoneme", "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 

wav2vec2\_xlsr50k\_english\_phoneme
===================================


This model is a fine-tuned version of facebook/wav2vec2-large-xlsr-53 on the TIMIT dataset.
It achieves the following results on the evaluation set:


* Loss: 0.5783
* Cer: 0.1178


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: 0.0003
* train\_batch\_size: 32
* eval\_batch\_size: 16
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 64
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 1000
* num\_epochs: 50
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.22.0.dev0
* Pytorch 1.12.1
* Datasets 1.13.3
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0003
* train\_batch\_size: 32
* eval\_batch\_size: 16
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 64
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 1000
* num\_epochs: 50
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.22.0.dev0
* Pytorch 1.12.1
* Datasets 1.13.3
* 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: 0.0003
* train\_batch\_size: 32
* eval\_batch\_size: 16
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 64
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 1000
* num\_epochs: 50
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.22.0.dev0
* Pytorch 1.12.1
* Datasets 1.13.3
* 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: 0.0003
* train\_batch\_size: 32
* eval\_batch\_size: 16
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 64
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 1000
* num\_epochs: 50
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.22.0.dev0
* Pytorch 1.12.1
* Datasets 1.13.3
* Tokenizers 0.12.1