
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# wav2vec2-large-xls-r-300m-gn

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1074
- Wer: 0.8952

## 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: 12
- eval_batch_size: 12
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 96
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 15
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 3.4445        | 0.45  | 400   | 0.6193          | 0.6606 |
| 0.4459        | 0.91  | 800   | 0.3260          | 0.3907 |
| 0.3307        | 1.36  | 1200  | 0.2739          | 0.3315 |
| 0.3049        | 1.81  | 1600  | 0.2565          | 0.3027 |
| 0.2688        | 2.27  | 2000  | 0.2526          | 0.2863 |
| 0.2589        | 2.72  | 2400  | 0.2426          | 0.2821 |
| 0.2608        | 3.17  | 2800  | 0.2513          | 0.2965 |
| 0.2384        | 3.62  | 3200  | 0.2555          | 0.3052 |
| 0.2504        | 4.08  | 3600  | 0.2462          | 0.2855 |
| 0.2193        | 4.53  | 4000  | 0.2367          | 0.2691 |
| 0.2177        | 4.99  | 4400  | 0.2313          | 0.2637 |
| 0.2029        | 5.44  | 4800  | 0.2344          | 0.2633 |
| 0.2032        | 5.89  | 5200  | 0.2248          | 0.2553 |
| 0.1921        | 6.35  | 5600  | 0.2286          | 0.2668 |
| 0.188         | 6.8   | 6000  | 0.2239          | 0.2550 |
| 0.1808        | 7.25  | 6400  | 0.2323          | 0.2546 |
| 0.1791        | 7.71  | 6800  | 0.2285          | 0.2500 |
| 0.1796        | 8.16  | 7200  | 0.2467          | 0.2653 |
| 0.3112        | 8.61  | 7600  | 0.3921          | 0.3988 |
| 0.3545        | 9.07  | 8000  | 0.3703          | 0.3951 |
| 0.2528        | 9.52  | 8400  | 0.2441          | 0.2764 |
| 0.1932        | 9.97  | 8800  | 0.2385          | 0.2659 |
| 0.1688        | 10.42 | 9200  | 0.2245          | 0.2413 |
| 0.1645        | 10.88 | 9600  | 0.2220          | 0.2396 |
| 0.1736        | 11.34 | 10000 | 0.2456          | 0.2421 |
| 0.3031        | 11.79 | 10400 | 0.4347          | 0.2643 |
| 0.5795        | 12.24 | 10800 | 0.6777          | 0.3291 |
| 0.7227        | 12.7  | 11200 | 0.6537          | 0.3372 |
| 0.8282        | 13.15 | 11600 | 1.0544          | 0.8223 |
| 0.9917        | 13.6  | 12000 | 1.0290          | 0.7793 |
| 0.9407        | 14.06 | 12400 | 1.0095          | 0.7090 |
| 1.1154        | 14.51 | 12800 | 1.1014          | 0.8454 |
| 1.1354        | 14.97 | 13200 | 1.1074          | 0.8952 |


### Framework versions

- Transformers 4.29.2
- Pytorch 2.0.1+cu117
- Datasets 2.12.0
- Tokenizers 0.13.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["wer"], "model-index": [{"name": "wav2vec2-large-xls-r-300m-gn", "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-xls-r-300m-gn
============================


This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 1.1074
* Wer: 0.8952


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: 12
* eval\_batch\_size: 12
* seed: 42
* gradient\_accumulation\_steps: 8
* total\_train\_batch\_size: 96
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 500
* num\_epochs: 15
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.29.2
* Pytorch 2.0.1+cu117
* Datasets 2.12.0
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0003
* train\_batch\_size: 12
* eval\_batch\_size: 12
* seed: 42
* gradient\_accumulation\_steps: 8
* total\_train\_batch\_size: 96
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 500
* num\_epochs: 15
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.29.2
* Pytorch 2.0.1+cu117
* Datasets 2.12.0
* Tokenizers 0.13.3
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: 0.0003
* train\_batch\_size: 12
* eval\_batch\_size: 12
* seed: 42
* gradient\_accumulation\_steps: 8
* total\_train\_batch\_size: 96
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 500
* num\_epochs: 15
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.29.2
* Pytorch 2.0.1+cu117
* Datasets 2.12.0
* Tokenizers 0.13.3