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# wav2vec2-10

This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 3.0354
- Wer: 1.0

## 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: 0.0003
- train_batch_size: 16
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 400
- num_epochs: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:---:|
| 4.2231        | 0.78  | 200  | 3.0442          | 1.0 |
| 2.8665        | 1.57  | 400  | 3.0081          | 1.0 |
| 2.8596        | 2.35  | 600  | 3.0905          | 1.0 |
| 2.865         | 3.14  | 800  | 3.0443          | 1.0 |
| 2.8613        | 3.92  | 1000 | 3.0316          | 1.0 |
| 2.8601        | 4.71  | 1200 | 3.0574          | 1.0 |
| 2.8554        | 5.49  | 1400 | 3.0261          | 1.0 |
| 2.8592        | 6.27  | 1600 | 3.0785          | 1.0 |
| 2.8606        | 7.06  | 1800 | 3.1129          | 1.0 |
| 2.8547        | 7.84  | 2000 | 3.0647          | 1.0 |
| 2.8565        | 8.63  | 2200 | 3.0624          | 1.0 |
| 2.8633        | 9.41  | 2400 | 2.9900          | 1.0 |
| 2.855         | 10.2  | 2600 | 3.0084          | 1.0 |
| 2.8581        | 10.98 | 2800 | 3.0092          | 1.0 |
| 2.8545        | 11.76 | 3000 | 3.0299          | 1.0 |
| 2.8583        | 12.55 | 3200 | 3.0293          | 1.0 |
| 2.8536        | 13.33 | 3400 | 3.0566          | 1.0 |
| 2.8556        | 14.12 | 3600 | 3.0385          | 1.0 |
| 2.8573        | 14.9  | 3800 | 3.0098          | 1.0 |
| 2.8551        | 15.69 | 4000 | 3.0623          | 1.0 |
| 2.8546        | 16.47 | 4200 | 3.0964          | 1.0 |
| 2.8569        | 17.25 | 4400 | 3.0648          | 1.0 |
| 2.8543        | 18.04 | 4600 | 3.0377          | 1.0 |
| 2.8532        | 18.82 | 4800 | 3.0454          | 1.0 |
| 2.8579        | 19.61 | 5000 | 3.0301          | 1.0 |
| 2.8532        | 20.39 | 5200 | 3.0364          | 1.0 |
| 2.852         | 21.18 | 5400 | 3.0187          | 1.0 |
| 2.8561        | 21.96 | 5600 | 3.0172          | 1.0 |
| 2.8509        | 22.75 | 5800 | 3.0420          | 1.0 |
| 2.8551        | 23.53 | 6000 | 3.0309          | 1.0 |
| 2.8552        | 24.31 | 6200 | 3.0416          | 1.0 |
| 2.8521        | 25.1  | 6400 | 3.0469          | 1.0 |
| 2.852         | 25.88 | 6600 | 3.0489          | 1.0 |
| 2.854         | 26.67 | 6800 | 3.0394          | 1.0 |
| 2.8572        | 27.45 | 7000 | 3.0336          | 1.0 |
| 2.8502        | 28.24 | 7200 | 3.0363          | 1.0 |
| 2.8557        | 29.02 | 7400 | 3.0304          | 1.0 |
| 2.8522        | 29.8  | 7600 | 3.0354          | 1.0 |


### Framework versions

- Transformers 4.19.2
- Pytorch 1.11.0+cu113
- Datasets 2.2.2
- Tokenizers 0.12.1

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "model-index": [{"name": "wav2vec2-10", "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 

wav2vec2-10
===========


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


* Loss: 3.0354
* Wer: 1.0


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: 0.0003
* train\_batch\_size: 16
* eval\_batch\_size: 4
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 400
* num\_epochs: 30


### Training results



### Framework versions


* Transformers 4.19.2
* Pytorch 1.11.0+cu113
* Datasets 2.2.2
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0003
* train\_batch\_size: 16
* eval\_batch\_size: 4
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 400
* num\_epochs: 30 ### Training results ### Framework versions


* Transformers 4.19.2
* Pytorch 1.11.0+cu113
* Datasets 2.2.2
* Tokenizers 0.12.1
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: 0.0003
* train\_batch\_size: 16
* eval\_batch\_size: 4
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 400
* num\_epochs: 30 ### Training results ### Framework versions


* Transformers 4.19.2
* Pytorch 1.11.0+cu113
* Datasets 2.2.2
* Tokenizers 0.12.1
passage: 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: 0.0003
* train\_batch\_size: 16
* eval\_batch\_size: 4
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 400
* num\_epochs: 30### Training results### Framework versions


* Transformers 4.19.2
* Pytorch 1.11.0+cu113
* Datasets 2.2.2
* Tokenizers 0.12.1