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# torgo_xlsr_finetune-M02-2

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: 2.1942
- Wer: 1.0791

## 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
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 30

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 23.2194       | 0.91  | 500   | 3.2975          | 0.9820 |
| 3.3856        | 1.81  | 1000  | 3.2225          | 0.9820 |
| 2.9403        | 2.72  | 1500  | 2.7805          | 0.9820 |
| 2.6255        | 3.62  | 2000  | 2.3830          | 0.9834 |
| 1.8901        | 4.53  | 2500  | 1.7920          | 1.3779 |
| 1.2594        | 5.43  | 3000  | 1.7845          | 1.3343 |
| 1.0008        | 6.34  | 3500  | 1.6923          | 1.3148 |
| 0.7896        | 7.25  | 4000  | 1.5444          | 1.2822 |
| 0.6373        | 8.15  | 4500  | 1.5547          | 1.2670 |
| 0.5639        | 9.06  | 5000  | 1.5924          | 1.1935 |
| 0.5           | 9.96  | 5500  | 1.7545          | 1.2060 |
| 0.4488        | 10.87 | 6000  | 1.6170          | 1.1498 |
| 0.3892        | 11.78 | 6500  | 1.7550          | 1.1664 |
| 0.3497        | 12.68 | 7000  | 1.9707          | 1.1845 |
| 0.3444        | 13.59 | 7500  | 1.8976          | 1.1657 |
| 0.3153        | 14.49 | 8000  | 1.9255          | 1.1415 |
| 0.2967        | 15.4  | 8500  | 1.8710          | 1.1470 |
| 0.2698        | 16.3  | 9000  | 1.7480          | 1.1408 |
| 0.2661        | 17.21 | 9500  | 1.8134          | 1.1123 |
| 0.255         | 18.12 | 10000 | 2.0806          | 1.1248 |
| 0.2021        | 19.02 | 10500 | 2.1426          | 1.1172 |
| 0.2179        | 19.93 | 11000 | 2.0832          | 1.1117 |
| 0.193         | 20.83 | 11500 | 2.3892          | 1.1262 |
| 0.1999        | 21.74 | 12000 | 2.1183          | 1.1096 |
| 0.1857        | 22.64 | 12500 | 1.9986          | 1.1047 |
| 0.1804        | 23.55 | 13000 | 2.0788          | 1.0978 |
| 0.1568        | 24.46 | 13500 | 2.2646          | 1.1026 |
| 0.1596        | 25.36 | 14000 | 2.0863          | 1.0673 |
| 0.1553        | 26.27 | 14500 | 2.1758          | 1.0804 |
| 0.1484        | 27.17 | 15000 | 2.0750          | 1.0693 |
| 0.1359        | 28.08 | 15500 | 2.1412          | 1.0784 |
| 0.131         | 28.99 | 16000 | 2.2616          | 1.0853 |
| 0.1386        | 29.89 | 16500 | 2.1942          | 1.0791 |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 1.18.3
- Tokenizers 0.13.2

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["wer"], "model-index": [{"name": "torgo_xlsr_finetune-M02-2", "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 

torgo\_xlsr\_finetune-M02-2
===========================


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: 2.1942
* Wer: 1.0791


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
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 1000
* num\_epochs: 30


### Training results



### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 1.18.3
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0001
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 1000
* num\_epochs: 30 ### Training results ### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 1.18.3
* Tokenizers 0.13.2
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
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 1000
* num\_epochs: 30 ### Training results ### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 1.18.3
* Tokenizers 0.13.2
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
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 1000
* num\_epochs: 30### Training results### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 1.18.3
* Tokenizers 0.13.2