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# wav2vec2-base-finetune-flickr8k

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: 3.0580
- 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: 0.0001
- train_batch_size: 12
- eval_batch_size: 2
- 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: 15
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:---:|
| 3.2252        | 0.8   | 500  | 3.0787          | 1.0 |
| 3.1958        | 1.6   | 1000 | 3.0698          | 1.0 |
| 3.1512        | 2.4   | 1500 | 3.0571          | 1.0 |
| 3.1411        | 3.2   | 2000 | 3.0578          | 1.0 |
| 3.1186        | 4.0   | 2500 | 3.0553          | 1.0 |
| 3.0852        | 4.8   | 3000 | 3.0616          | 1.0 |
| 3.1063        | 5.6   | 3500 | 3.0621          | 1.0 |
| 3.0678        | 6.4   | 4000 | 3.0550          | 1.0 |
| 3.0239        | 7.2   | 4500 | 3.0592          | 1.0 |
| 3.0321        | 8.0   | 5000 | 3.0652          | 1.0 |
| 3.0396        | 8.8   | 5500 | 3.0542          | 1.0 |
| 3.0723        | 9.6   | 6000 | 3.0552          | 1.0 |
| 3.0567        | 10.4  | 6500 | 3.0545          | 1.0 |
| 3.0438        | 11.2  | 7000 | 3.0611          | 1.0 |
| 3.073         | 12.0  | 7500 | 3.0548          | 1.0 |
| 3.0293        | 12.8  | 8000 | 3.0585          | 1.0 |
| 3.0444        | 13.6  | 8500 | 3.0571          | 1.0 |
| 3.0213        | 14.4  | 9000 | 3.0580          | 1.0 |


### Framework versions

- Transformers 4.27.4
- Pytorch 2.0.0
- Datasets 2.11.0
- Tokenizers 0.13.2

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["wer"], "model-index": [{"name": "wav2vec2-base-finetune-flickr8k", "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 

wav2vec2-base-finetune-flickr8k
===============================


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: 3.0580
* 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: 0.0001
* train\_batch\_size: 12
* eval\_batch\_size: 2
* 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: 15
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.27.4
* Pytorch 2.0.0
* Datasets 2.11.0
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0001
* train\_batch\_size: 12
* eval\_batch\_size: 2
* 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: 15
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.27.4
* Pytorch 2.0.0
* Datasets 2.11.0
* 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: 12
* eval\_batch\_size: 2
* 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: 15
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.27.4
* Pytorch 2.0.0
* Datasets 2.11.0
* 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: 12
* eval\_batch\_size: 2
* 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: 15
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.27.4
* Pytorch 2.0.0
* Datasets 2.11.0
* Tokenizers 0.13.2