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# wav2vec2-large-xlsr-53_toy_train_data_augment_0.1

This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4658
- Wer: 0.5037

## 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
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 3.447         | 1.05  | 250  | 3.3799          | 1.0    |
| 3.089         | 2.1   | 500  | 3.4868          | 1.0    |
| 3.063         | 3.15  | 750  | 3.3155          | 1.0    |
| 2.4008        | 4.2   | 1000 | 1.2934          | 0.8919 |
| 1.618         | 5.25  | 1250 | 0.7847          | 0.7338 |
| 1.3038        | 6.3   | 1500 | 0.6459          | 0.6712 |
| 1.2074        | 7.35  | 1750 | 0.5705          | 0.6269 |
| 1.1062        | 8.4   | 2000 | 0.5267          | 0.5843 |
| 1.026         | 9.45  | 2250 | 0.5108          | 0.5683 |
| 0.9505        | 10.5  | 2500 | 0.5066          | 0.5568 |
| 0.893         | 11.55 | 2750 | 0.5161          | 0.5532 |
| 0.8535        | 12.6  | 3000 | 0.4994          | 0.5341 |
| 0.8462        | 13.65 | 3250 | 0.4626          | 0.5262 |
| 0.8334        | 14.7  | 3500 | 0.4593          | 0.5197 |
| 0.842         | 15.75 | 3750 | 0.4651          | 0.5126 |
| 0.7678        | 16.81 | 4000 | 0.4687          | 0.5120 |
| 0.7873        | 17.86 | 4250 | 0.4716          | 0.5070 |
| 0.7486        | 18.91 | 4500 | 0.4657          | 0.5033 |
| 0.7073        | 19.96 | 4750 | 0.4658          | 0.5037 |


### Framework versions

- Transformers 4.17.0
- Pytorch 1.11.0+cu102
- Datasets 2.0.0
- Tokenizers 0.11.6

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "model-index": [{"name": "wav2vec2-large-xlsr-53_toy_train_data_augment_0.1", "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-xlsr-53\_toy\_train\_data\_augment\_0.1
======================================================


This model is a fine-tuned version of facebook/wav2vec2-large-xlsr-53 on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 0.4658
* Wer: 0.5037


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
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 16
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 1000
* num\_epochs: 20


### Training results



### Framework versions


* Transformers 4.17.0
* Pytorch 1.11.0+cu102
* Datasets 2.0.0
* Tokenizers 0.11.6



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0001
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 16
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 1000
* num\_epochs: 20 ### Training results ### Framework versions


* Transformers 4.17.0
* Pytorch 1.11.0+cu102
* Datasets 2.0.0
* Tokenizers 0.11.6
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: 8
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 16
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 1000
* num\_epochs: 20 ### Training results ### Framework versions


* Transformers 4.17.0
* Pytorch 1.11.0+cu102
* Datasets 2.0.0
* Tokenizers 0.11.6
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: 8
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 16
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 1000
* num\_epochs: 20### Training results### Framework versions


* Transformers 4.17.0
* Pytorch 1.11.0+cu102
* Datasets 2.0.0
* Tokenizers 0.11.6