
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# wav2vec2_finetuned_on_grid

This model is a fine-tuned version of [facebook/wav2vec2-base-960h](https://huggingface.co/facebook/wav2vec2-base-960h) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3047
- Wer: 0.7993
- Cer: 0.5300

## 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: 0.001
- train_batch_size: 16
- 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: 500
- num_epochs: 30

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer    | Cer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|
| 6.8952        | 1.43  | 500   | 0.4457          | 0.7814 | 0.2382 |
| 0.8573        | 2.86  | 1000  | 0.3487          | 0.7846 | 0.4142 |
| 0.6617        | 4.29  | 1500  | 0.3471          | 0.7759 | 0.4080 |
| 0.5865        | 5.71  | 2000  | 0.3279          | 0.8131 | 0.5024 |
| 0.5855        | 7.14  | 2500  | 0.3384          | 0.7841 | 0.4356 |
| 0.554         | 8.57  | 3000  | 0.3230          | 0.7949 | 0.4626 |
| 0.5527        | 10.0  | 3500  | 0.3244          | 0.7706 | 0.4572 |
| 0.5224        | 11.43 | 4000  | 0.3197          | 0.7878 | 0.4891 |
| 0.5112        | 12.86 | 4500  | 0.3180          | 0.7939 | 0.4989 |
| 0.5037        | 14.29 | 5000  | 0.3234          | 0.7650 | 0.4987 |
| 0.5115        | 15.71 | 5500  | 0.3153          | 0.7712 | 0.4899 |
| 0.498         | 17.14 | 6000  | 0.3168          | 0.7649 | 0.4728 |
| 0.5031        | 18.57 | 6500  | 0.3138          | 0.7619 | 0.5011 |
| 0.4936        | 20.0  | 7000  | 0.3157          | 0.7575 | 0.5112 |
| 0.4935        | 21.43 | 7500  | 0.3140          | 0.7583 | 0.4985 |
| 0.495         | 22.86 | 8000  | 0.3080          | 0.7672 | 0.5257 |
| 0.4916        | 24.29 | 8500  | 0.3075          | 0.7782 | 0.5509 |
| 0.4897        | 25.71 | 9000  | 0.3053          | 0.7858 | 0.5241 |
| 0.4845        | 27.14 | 9500  | 0.3042          | 0.8001 | 0.5380 |
| 0.4894        | 28.57 | 10000 | 0.3038          | 0.8018 | 0.5462 |
| 0.4823        | 30.0  | 10500 | 0.3047          | 0.7993 | 0.5300 |


### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["wer"], "model-index": [{"name": "wav2vec2_finetuned_on_grid", "results": []}]}
transformers pytorch tensorboard wav2vec2 automatic-speech-recognition generated_from_trainer license:apache-2.0 endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #generated_from_trainer #license-apache-2.0 #endpoints_compatible #region-us 

wav2vec2\_finetuned\_on\_grid
=============================


This model is a fine-tuned version of facebook/wav2vec2-base-960h on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 0.3047
* Wer: 0.7993
* Cer: 0.5300


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: 0.001
* train\_batch\_size: 16
* 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: 500
* num\_epochs: 30


### Training results



### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.11.0
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.001
* train\_batch\_size: 16
* 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: 500
* num\_epochs: 30 ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.11.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #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: 0.001
* train\_batch\_size: 16
* 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: 500
* num\_epochs: 30 ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.11.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #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: 0.001
* train\_batch\_size: 16
* 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: 500
* num\_epochs: 30### Training results### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.11.0
* Tokenizers 0.13.3