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# dat259-wav2vec2-en2

This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the common_voice_1_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4036
- Wer: 0.5090

## 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: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 300
- num_epochs: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 4.4355        | 1.82  | 200  | 3.0307          | 1.0    |
| 2.1744        | 3.64  | 400  | 1.5661          | 0.7449 |
| 0.5535        | 5.45  | 600  | 1.3005          | 0.5914 |
| 0.3248        | 7.27  | 800  | 1.2481          | 0.5690 |
| 0.2297        | 9.09  | 1000 | 1.2810          | 0.5366 |
| 0.18          | 10.91 | 1200 | 1.3481          | 0.5378 |
| 0.1499        | 12.73 | 1400 | 1.3124          | 0.5350 |
| 0.1283        | 14.55 | 1600 | 1.3668          | 0.5161 |
| 0.1089        | 16.36 | 1800 | 1.3833          | 0.5109 |
| 0.0973        | 18.18 | 2000 | 1.3876          | 0.5075 |
| 0.0897        | 20.0  | 2200 | 1.4036          | 0.5090 |


### Framework versions

- Transformers 4.21.1
- Pytorch 1.12.1+cu102
- Datasets 2.4.0
- Tokenizers 0.12.1

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["common_voice_1_0"], "model-index": [{"name": "dat259-wav2vec2-en2", "results": []}]}
transformers pytorch wav2vec2 automatic-speech-recognition generated_from_trainer dataset:common_voice_1_0 license:apache-2.0 endpoints_compatible region:us
TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #generated_from_trainer #dataset-common_voice_1_0 #license-apache-2.0 #endpoints_compatible #region-us 

dat259-wav2vec2-en2
===================


This model is a fine-tuned version of facebook/wav2vec2-base on the common\_voice\_1\_0 dataset.
It achieves the following results on the evaluation set:


* Loss: 1.4036
* Wer: 0.5090


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: 16
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 32
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 300
* num\_epochs: 20
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.21.1
* Pytorch 1.12.1+cu102
* Datasets 2.4.0
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0001
* train\_batch\_size: 16
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 32
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 300
* num\_epochs: 20
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.21.1
* Pytorch 1.12.1+cu102
* Datasets 2.4.0
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #generated_from_trainer #dataset-common_voice_1_0 #license-apache-2.0 #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0001
* train\_batch\_size: 16
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 32
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 300
* num\_epochs: 20
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.21.1
* Pytorch 1.12.1+cu102
* Datasets 2.4.0
* Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #generated_from_trainer #dataset-common_voice_1_0 #license-apache-2.0 #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0001
* train\_batch\_size: 16
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 32
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 300
* num\_epochs: 20
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.21.1
* Pytorch 1.12.1+cu102
* Datasets 2.4.0
* Tokenizers 0.12.1