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# wav2vec2-large-xls-hun-53h-colab

This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the common_voice dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6027
- Wer: 0.4618

## 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: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 23
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 13.4225       | 0.67  | 100  | 3.7750          | 1.0    |
| 3.4121        | 1.34  | 200  | 3.3166          | 1.0    |
| 3.2263        | 2.01  | 300  | 3.1403          | 1.0    |
| 3.0038        | 2.68  | 400  | 2.2474          | 0.9990 |
| 1.2243        | 3.35  | 500  | 0.8174          | 0.7666 |
| 0.6368        | 4.03  | 600  | 0.6306          | 0.6633 |
| 0.4426        | 4.7   | 700  | 0.6151          | 0.6648 |
| 0.3821        | 5.37  | 800  | 0.5765          | 0.6138 |
| 0.3337        | 6.04  | 900  | 0.5522          | 0.5785 |
| 0.2832        | 6.71  | 1000 | 0.5822          | 0.5691 |
| 0.2485        | 7.38  | 1100 | 0.5626          | 0.5449 |
| 0.2335        | 8.05  | 1200 | 0.5866          | 0.5662 |
| 0.2031        | 8.72  | 1300 | 0.5574          | 0.5420 |
| 0.1925        | 9.39  | 1400 | 0.5572          | 0.5297 |
| 0.1793        | 10.07 | 1500 | 0.5878          | 0.5185 |
| 0.1652        | 10.74 | 1600 | 0.6173          | 0.5243 |
| 0.1663        | 11.41 | 1700 | 0.5807          | 0.5133 |
| 0.1544        | 12.08 | 1800 | 0.5979          | 0.5154 |
| 0.148         | 12.75 | 1900 | 0.5545          | 0.4986 |
| 0.138         | 13.42 | 2000 | 0.5798          | 0.4947 |
| 0.1353        | 14.09 | 2100 | 0.5670          | 0.5028 |
| 0.1283        | 14.76 | 2200 | 0.5862          | 0.4957 |
| 0.1271        | 15.43 | 2300 | 0.6009          | 0.4961 |
| 0.1108        | 16.11 | 2400 | 0.5873          | 0.4975 |
| 0.1182        | 16.78 | 2500 | 0.6013          | 0.4893 |
| 0.103         | 17.45 | 2600 | 0.6165          | 0.4898 |
| 0.1084        | 18.12 | 2700 | 0.6186          | 0.4838 |
| 0.1014        | 18.79 | 2800 | 0.6122          | 0.4767 |
| 0.1009        | 19.46 | 2900 | 0.5981          | 0.4793 |
| 0.1004        | 20.13 | 3000 | 0.6034          | 0.4770 |
| 0.0922        | 20.8  | 3100 | 0.6127          | 0.4663 |
| 0.09          | 21.47 | 3200 | 0.5967          | 0.4672 |
| 0.0893        | 22.15 | 3300 | 0.6051          | 0.4611 |
| 0.0817        | 22.82 | 3400 | 0.6027          | 0.4618 |


### Framework versions

- Transformers 4.11.3
- Pytorch 1.10.0+cu113
- Datasets 1.18.3
- Tokenizers 0.10.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["common_voice"], "model-index": [{"name": "wav2vec2-large-xls-hun-53h-colab", "results": []}]}
transformers pytorch tensorboard wav2vec2 automatic-speech-recognition generated_from_trainer dataset:common_voice license:apache-2.0 endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #generated_from_trainer #dataset-common_voice #license-apache-2.0 #endpoints_compatible #region-us 

wav2vec2-large-xls-hun-53h-colab
================================


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


* Loss: 0.6027
* Wer: 0.4618


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: 16
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 32
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 500
* num\_epochs: 23
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.11.3
* Pytorch 1.10.0+cu113
* Datasets 1.18.3
* Tokenizers 0.10.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0003
* train\_batch\_size: 16
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 32
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 500
* num\_epochs: 23
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.11.3
* Pytorch 1.10.0+cu113
* Datasets 1.18.3
* Tokenizers 0.10.3
TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #generated_from_trainer #dataset-common_voice #license-apache-2.0 #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0003
* train\_batch\_size: 16
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 32
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 500
* num\_epochs: 23
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.11.3
* Pytorch 1.10.0+cu113
* Datasets 1.18.3
* Tokenizers 0.10.3
passage: TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #generated_from_trainer #dataset-common_voice #license-apache-2.0 #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0003
* train\_batch\_size: 16
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 32
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 500
* num\_epochs: 23
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.11.3
* Pytorch 1.10.0+cu113
* Datasets 1.18.3
* Tokenizers 0.10.3