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# wav2vec2-base-ft

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: 0.0156
- Accuracy: 0.9964

## 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: 1e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step  | Accuracy | Validation Loss |
|:-------------:|:-----:|:-----:|:--------:|:---------------:|
| 0.0905        | 1.0   | 8558  | 0.9952   | 0.0197          |
| 0.0572        | 2.0   | 17117 | 0.9964   | 0.0156          |
| 0.0597        | 3.0   | 25674 | 0.9955   | 0.0181          |
| 0.0396        | 4.0   | 34232 | 0.9950   | 0.0207          |
| 0.0399        | 5.0   | 42790 | 0.9938   | 0.0249          |


### Framework versions

- Transformers 4.27.2
- Pytorch 1.11.0
- Datasets 2.10.1
- Tokenizers 0.12.1
{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["mazkooleg/0-9up_google_speech_commands_augmented_raw"], "metrics": ["accuracy"], "model-index": [{"name": "wav2vec2-base-ft", "results": []}]}
transformers pytorch wav2vec2 audio-classification generated_from_trainer dataset:mazkooleg/0-9up_google_speech_commands_augmented_raw license:apache-2.0 endpoints_compatible region:us
TAGS
#transformers #pytorch #wav2vec2 #audio-classification #generated_from_trainer #dataset-mazkooleg/0-9up_google_speech_commands_augmented_raw #license-apache-2.0 #endpoints_compatible #region-us 

wav2vec2-base-ft
================


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: 0.0156
* Accuracy: 0.9964


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: 1e-05
* train\_batch\_size: 32
* eval\_batch\_size: 32
* seed: 42
* gradient\_accumulation\_steps: 4
* total\_train\_batch\_size: 128
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.1
* num\_epochs: 5


### Training results



### Framework versions


* Transformers 4.27.2
* Pytorch 1.11.0
* Datasets 2.10.1
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1e-05
* train\_batch\_size: 32
* eval\_batch\_size: 32
* seed: 42
* gradient\_accumulation\_steps: 4
* total\_train\_batch\_size: 128
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.1
* num\_epochs: 5 ### Training results ### Framework versions


* Transformers 4.27.2
* Pytorch 1.11.0
* Datasets 2.10.1
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #wav2vec2 #audio-classification #generated_from_trainer #dataset-mazkooleg/0-9up_google_speech_commands_augmented_raw #license-apache-2.0 #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1e-05
* train\_batch\_size: 32
* eval\_batch\_size: 32
* seed: 42
* gradient\_accumulation\_steps: 4
* total\_train\_batch\_size: 128
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.1
* num\_epochs: 5 ### Training results ### Framework versions


* Transformers 4.27.2
* Pytorch 1.11.0
* Datasets 2.10.1
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #wav2vec2 #audio-classification #generated_from_trainer #dataset-mazkooleg/0-9up_google_speech_commands_augmented_raw #license-apache-2.0 #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1e-05
* train\_batch\_size: 32
* eval\_batch\_size: 32
* seed: 42
* gradient\_accumulation\_steps: 4
* total\_train\_batch\_size: 128
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.1
* num\_epochs: 5### Training results### Framework versions


* Transformers 4.27.2
* Pytorch 1.11.0
* Datasets 2.10.1
* Tokenizers 0.12.1