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# wav2vec2-large-xlsr-53_train_data_full

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: 0.4168
- Wer: 0.3383

## 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: 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: 1000
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 3.0459        | 0.73  | 500   | 3.2037          | 0.9995 |
| 0.7938        | 1.45  | 1000  | 0.7432          | 0.6373 |
| 0.503         | 2.18  | 1500  | 0.5517          | 0.5115 |
| 0.4475        | 2.91  | 2000  | 0.4916          | 0.4624 |
| 0.3575        | 3.63  | 2500  | 0.4612          | 0.4362 |
| 0.3206        | 4.36  | 3000  | 0.4546          | 0.4198 |
| 0.3155        | 5.09  | 3500  | 0.4073          | 0.3929 |
| 0.2827        | 5.81  | 4000  | 0.4172          | 0.3808 |
| 0.2575        | 6.54  | 4500  | 0.4183          | 0.3741 |
| 0.2399        | 7.27  | 5000  | 0.4181          | 0.3680 |
| 0.2455        | 7.99  | 5500  | 0.3981          | 0.3604 |
| 0.2512        | 8.72  | 6000  | 0.4203          | 0.3612 |
| 0.221         | 9.45  | 6500  | 0.4073          | 0.3560 |
| 0.19          | 10.17 | 7000  | 0.4206          | 0.3547 |
| 0.207         | 10.9  | 7500  | 0.3992          | 0.3517 |
| 0.187         | 11.63 | 8000  | 0.4078          | 0.3517 |
| 0.2029        | 12.35 | 8500  | 0.4143          | 0.3469 |
| 0.171         | 13.08 | 9000  | 0.4007          | 0.3430 |
| 0.1658        | 13.81 | 9500  | 0.3862          | 0.3422 |
| 0.2021        | 14.53 | 10000 | 0.4132          | 0.3454 |
| 0.165         | 15.26 | 10500 | 0.3997          | 0.3407 |
| 0.1562        | 15.99 | 11000 | 0.4069          | 0.3416 |
| 0.1613        | 16.71 | 11500 | 0.4040          | 0.3393 |
| 0.1713        | 17.44 | 12000 | 0.4094          | 0.3411 |
| 0.1541        | 18.17 | 12500 | 0.4043          | 0.3367 |
| 0.144         | 18.89 | 13000 | 0.4086          | 0.3374 |
| 0.1483        | 19.62 | 13500 | 0.4168          | 0.3383 |


### Framework versions

- Transformers 4.18.0
- Pytorch 1.11.0+cu102
- Datasets 2.1.0
- Tokenizers 0.12.1

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "model-index": [{"name": "wav2vec2-large-xlsr-53_train_data_full", "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\_train\_data\_full
=========================================


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: 0.4168
* Wer: 0.3383


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: 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: 1000
* num\_epochs: 20


### Training results



### Framework versions


* Transformers 4.18.0
* Pytorch 1.11.0+cu102
* Datasets 2.1.0
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0001
* 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: 1000
* num\_epochs: 20 ### Training results ### Framework versions


* Transformers 4.18.0
* Pytorch 1.11.0+cu102
* Datasets 2.1.0
* 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: 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: 1000
* num\_epochs: 20 ### Training results ### Framework versions


* Transformers 4.18.0
* Pytorch 1.11.0+cu102
* Datasets 2.1.0
* Tokenizers 0.12.1
passage: 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: 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: 1000
* num\_epochs: 20### Training results### Framework versions


* Transformers 4.18.0
* Pytorch 1.11.0+cu102
* Datasets 2.1.0
* Tokenizers 0.12.1