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# wav2vec2-base-sound2

This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5012
- Accuracy: 0.5357

## 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: 9e-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: 25

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 1    | 2.0762          | 0.0714   |
| No log        | 2.0   | 2    | 2.0638          | 0.1429   |
| No log        | 3.0   | 3    | 2.0387          | 0.2143   |
| No log        | 4.0   | 4    | 2.0124          | 0.2143   |
| No log        | 5.0   | 5    | 1.9864          | 0.2143   |
| No log        | 6.0   | 6    | 1.9609          | 0.2143   |
| No log        | 7.0   | 7    | 1.9235          | 0.2143   |
| No log        | 8.0   | 8    | 1.9379          | 0.2143   |
| No log        | 9.0   | 9    | 1.8627          | 0.2857   |
| 1.9713        | 10.0  | 10   | 1.8277          | 0.3214   |
| 1.9713        | 11.0  | 11   | 1.7765          | 0.3571   |
| 1.9713        | 12.0  | 12   | 1.7204          | 0.5      |
| 1.9713        | 13.0  | 13   | 1.6956          | 0.5      |
| 1.9713        | 14.0  | 14   | 1.6602          | 0.5357   |
| 1.9713        | 15.0  | 15   | 1.6277          | 0.5714   |
| 1.9713        | 16.0  | 16   | 1.6053          | 0.5      |
| 1.9713        | 17.0  | 17   | 1.5825          | 0.5      |
| 1.9713        | 18.0  | 18   | 1.5656          | 0.4286   |
| 1.9713        | 19.0  | 19   | 1.5616          | 0.4643   |
| 1.6334        | 20.0  | 20   | 1.5613          | 0.4286   |
| 1.6334        | 21.0  | 21   | 1.5419          | 0.5      |
| 1.6334        | 22.0  | 22   | 1.5166          | 0.5357   |
| 1.6334        | 23.0  | 23   | 1.5088          | 0.5      |
| 1.6334        | 24.0  | 24   | 1.5052          | 0.5      |
| 1.6334        | 25.0  | 25   | 1.5012          | 0.5357   |


### Framework versions

- Transformers 4.18.0
- Pytorch 1.11.0+cu113
- Datasets 1.14.0
- Tokenizers 0.12.1

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "model-index": [{"name": "wav2vec2-base-sound2", "results": []}]}
transformers pytorch tensorboard wav2vec2 audio-classification generated_from_trainer license:apache-2.0 endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #wav2vec2 #audio-classification #generated_from_trainer #license-apache-2.0 #endpoints_compatible #region-us 

wav2vec2-base-sound2
====================


This model is a fine-tuned version of facebook/wav2vec2-base on an unknown dataset.
It achieves the following results on the evaluation set:


* Loss: 1.5012
* Accuracy: 0.5357


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: 9e-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: 25


### Training results



### Framework versions


* Transformers 4.18.0
* Pytorch 1.11.0+cu113
* Datasets 1.14.0
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 9e-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: 25 ### Training results ### Framework versions


* Transformers 4.18.0
* Pytorch 1.11.0+cu113
* Datasets 1.14.0
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #wav2vec2 #audio-classification #generated_from_trainer #license-apache-2.0 #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 9e-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: 25 ### Training results ### Framework versions


* Transformers 4.18.0
* Pytorch 1.11.0+cu113
* Datasets 1.14.0
* Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #tensorboard #wav2vec2 #audio-classification #generated_from_trainer #license-apache-2.0 #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 9e-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: 25### Training results### Framework versions


* Transformers 4.18.0
* Pytorch 1.11.0+cu113
* Datasets 1.14.0
* Tokenizers 0.12.1