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# wav2vec2-base-100k-voxpopuli-finetuned-gtzan

This model is a fine-tuned version of [facebook/wav2vec2-base-100k-voxpopuli](https://huggingface.co/facebook/wav2vec2-base-100k-voxpopuli) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9408
- Accuracy: 0.86

## 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: 5e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 225  | 2.1672          | 0.3      |
| 2.1675        | 2.0   | 450  | 2.0095          | 0.29     |
| 2.1675        | 3.0   | 675  | 1.7326          | 0.29     |
| 1.7199        | 4.0   | 900  | 1.4980          | 0.49     |
| 1.7199        | 5.0   | 1125 | 1.4088          | 0.37     |
| 1.3585        | 6.0   | 1350 | 1.2238          | 0.54     |
| 1.3585        | 7.0   | 1575 | 1.3579          | 0.52     |
| 1.0599        | 8.0   | 1800 | 0.9954          | 0.62     |
| 1.0599        | 9.0   | 2025 | 0.9543          | 0.73     |
| 0.8337        | 10.0  | 2250 | 0.9428          | 0.76     |
| 0.8337        | 11.0  | 2475 | 0.8810          | 0.78     |
| 0.5861        | 12.0  | 2700 | 0.7753          | 0.76     |
| 0.5861        | 13.0  | 2925 | 0.9981          | 0.74     |
| 0.3662        | 14.0  | 3150 | 1.1597          | 0.77     |
| 0.3662        | 15.0  | 3375 | 1.0466          | 0.79     |
| 0.277         | 16.0  | 3600 | 1.0763          | 0.81     |
| 0.277         | 17.0  | 3825 | 0.8407          | 0.87     |
| 0.1731        | 18.0  | 4050 | 0.9317          | 0.86     |
| 0.1731        | 19.0  | 4275 | 0.8545          | 0.87     |
| 0.1489        | 20.0  | 4500 | 0.9408          | 0.86     |


### Framework versions

- Transformers 4.17.0
- Pytorch 1.10.2
- Datasets 1.18.4
- Tokenizers 0.11.6

{"license": "cc-by-nc-4.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "model-index": [{"name": "wav2vec2-base-100k-voxpopuli-finetuned-gtzan", "results": []}]}
transformers pytorch wav2vec2 audio-classification generated_from_trainer license:cc-by-nc-4.0 endpoints_compatible region:us
TAGS
#transformers #pytorch #wav2vec2 #audio-classification #generated_from_trainer #license-cc-by-nc-4.0 #endpoints_compatible #region-us 

wav2vec2-base-100k-voxpopuli-finetuned-gtzan
============================================


This model is a fine-tuned version of facebook/wav2vec2-base-100k-voxpopuli on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 0.9408
* Accuracy: 0.86


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: 5e-05
* train\_batch\_size: 2
* eval\_batch\_size: 2
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 4
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.1
* num\_epochs: 20
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.17.0
* Pytorch 1.10.2
* Datasets 1.18.4
* Tokenizers 0.11.6



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 2
* eval\_batch\_size: 2
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 4
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.1
* num\_epochs: 20
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.17.0
* Pytorch 1.10.2
* Datasets 1.18.4
* Tokenizers 0.11.6
TAGS
#transformers #pytorch #wav2vec2 #audio-classification #generated_from_trainer #license-cc-by-nc-4.0 #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 2
* eval\_batch\_size: 2
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 4
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.1
* num\_epochs: 20
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.17.0
* Pytorch 1.10.2
* Datasets 1.18.4
* Tokenizers 0.11.6
passage: TAGS
#transformers #pytorch #wav2vec2 #audio-classification #generated_from_trainer #license-cc-by-nc-4.0 #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 2
* eval\_batch\_size: 2
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 4
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.1
* num\_epochs: 20
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.17.0
* Pytorch 1.10.2
* Datasets 1.18.4
* Tokenizers 0.11.6