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# torgo_xlsr_finetune-M03-2

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: 0.2376
- Wer: 0.5541

## 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    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 23.6177       | 0.92  | 500   | 3.4289          | 1.0    |
| 3.4209        | 1.85  | 1000  | 21.5765         | 1.0    |
| 3.1586        | 2.77  | 1500  | 2.8397          | 1.0    |
| 2.7993        | 3.69  | 2000  | 2.7192          | 1.2867 |
| 2.644         | 4.61  | 2500  | 2.5331          | 1.2996 |
| 2.4662        | 5.54  | 3000  | 2.1750          | 1.2341 |
| 1.9879        | 6.46  | 3500  | 1.3732          | 1.2693 |
| 1.4941        | 7.38  | 4000  | 0.8590          | 1.1900 |
| 1.1848        | 8.3   | 4500  | 0.6774          | 1.1339 |
| 0.9662        | 9.23  | 5000  | 0.5184          | 0.9856 |
| 0.8094        | 10.15 | 5500  | 0.4515          | 0.9504 |
| 0.6835        | 11.07 | 6000  | 0.3616          | 0.8457 |
| 0.6111        | 11.99 | 6500  | 0.3209          | 0.8254 |
| 0.5305        | 12.92 | 7000  | 0.3098          | 0.7902 |
| 0.479         | 13.84 | 7500  | 0.2964          | 0.7569 |
| 0.4369        | 14.76 | 8000  | 0.2447          | 0.7063 |
| 0.3836        | 15.68 | 8500  | 0.2676          | 0.7063 |
| 0.3628        | 16.61 | 9000  | 0.2714          | 0.7128 |
| 0.3416        | 17.53 | 9500  | 0.2664          | 0.6766 |
| 0.3297        | 18.45 | 10000 | 0.2510          | 0.6528 |
| 0.2883        | 19.37 | 10500 | 0.2636          | 0.6493 |
| 0.2694        | 20.3  | 11000 | 0.2556          | 0.6255 |
| 0.2655        | 21.22 | 11500 | 0.2328          | 0.6186 |
| 0.2364        | 22.14 | 12000 | 0.2293          | 0.6037 |
| 0.241         | 23.06 | 12500 | 0.2587          | 0.5928 |
| 0.2125        | 23.99 | 13000 | 0.2528          | 0.5843 |
| 0.2101        | 24.91 | 13500 | 0.2315          | 0.5719 |
| 0.1973        | 25.83 | 14000 | 0.2401          | 0.5769 |
| 0.1914        | 26.75 | 14500 | 0.2380          | 0.5610 |
| 0.1936        | 27.68 | 15000 | 0.2425          | 0.5551 |
| 0.1808        | 28.6  | 15500 | 0.2425          | 0.5556 |
| 0.1739        | 29.52 | 16000 | 0.2376          | 0.5541 |


### 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-M03-2", "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-M03-2
===========================


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: 0.2376
* Wer: 0.5541


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