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# torgo_xlsr_finetune-M05-2

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: 1.5128
- Wer: 1.1148

## 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    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 22.2047       | 0.86  | 500   | 3.3446          | 0.9930 |
| 3.3679        | 1.72  | 1000  | 2.9591          | 0.9930 |
| 2.8813        | 2.58  | 1500  | 2.7978          | 0.9930 |
| 2.7207        | 3.44  | 2000  | 2.5604          | 0.9930 |
| 2.3274        | 4.3   | 2500  | 2.0135          | 1.4468 |
| 1.5821        | 5.16  | 3000  | 1.6148          | 1.5686 |
| 1.1549        | 6.02  | 3500  | 1.3447          | 1.5014 |
| 0.8908        | 6.88  | 4000  | 1.3315          | 1.4524 |
| 0.7204        | 7.75  | 4500  | 1.3250          | 1.3894 |
| 0.6209        | 8.61  | 5000  | 1.2566          | 1.3697 |
| 0.5507        | 9.47  | 5500  | 1.2300          | 1.3221 |
| 0.4622        | 10.33 | 6000  | 1.3826          | 1.3165 |
| 0.4503        | 11.19 | 6500  | 1.2769          | 1.2717 |
| 0.4026        | 12.05 | 7000  | 1.3531          | 1.2955 |
| 0.3617        | 12.91 | 7500  | 1.2806          | 1.2521 |
| 0.3239        | 13.77 | 8000  | 1.5507          | 1.2437 |
| 0.3051        | 14.63 | 8500  | 1.6217          | 1.2563 |
| 0.2983        | 15.49 | 9000  | 1.5210          | 1.2185 |
| 0.2766        | 16.35 | 9500  | 1.4787          | 1.2143 |
| 0.2642        | 17.21 | 10000 | 1.6284          | 1.2311 |
| 0.2358        | 18.07 | 10500 | 1.3203          | 1.1891 |
| 0.2303        | 18.93 | 11000 | 1.5233          | 1.2185 |
| 0.2166        | 19.79 | 11500 | 1.5111          | 1.2129 |
| 0.2162        | 20.65 | 12000 | 1.5128          | 1.1919 |
| 0.1981        | 21.51 | 12500 | 1.4668          | 1.1877 |
| 0.1736        | 22.38 | 13000 | 1.5041          | 1.1485 |
| 0.1725        | 23.24 | 13500 | 1.5306          | 1.1639 |
| 0.1632        | 24.1  | 14000 | 1.3756          | 1.1373 |
| 0.1597        | 24.96 | 14500 | 1.5404          | 1.1345 |
| 0.1571        | 25.82 | 15000 | 1.4863          | 1.1359 |
| 0.1569        | 26.68 | 15500 | 1.4775          | 1.1401 |
| 0.1431        | 27.54 | 16000 | 1.5410          | 1.1218 |
| 0.1373        | 28.4  | 16500 | 1.5212          | 1.1246 |
| 0.1461        | 29.26 | 17000 | 1.5128          | 1.1148 |


### 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-M05-2", "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-M05-2
===========================


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: 1.5128
* Wer: 1.1148


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