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# wav2vec2-finetuned-on-shEMO

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: 1.0218
- Accuracy: 0.8

## 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: 3e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- 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

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.4581        | 1.0   | 75   | 1.4405          | 0.5767   |
| 1.0505        | 2.0   | 150  | 0.9797          | 0.71     |
| 0.9486        | 3.0   | 225  | 0.8445          | 0.74     |
| 0.7795        | 4.0   | 300  | 0.9015          | 0.6867   |
| 0.6058        | 5.0   | 375  | 0.7416          | 0.7767   |
| 0.5169        | 6.0   | 450  | 0.7565          | 0.78     |
| 0.4251        | 7.0   | 525  | 0.6422          | 0.82     |
| 0.3567        | 8.0   | 600  | 0.5284          | 0.8367   |
| 0.2806        | 9.0   | 675  | 0.6506          | 0.8033   |
| 0.2108        | 10.0  | 750  | 0.6477          | 0.8333   |
| 0.1468        | 11.0  | 825  | 0.5919          | 0.85     |
| 0.1624        | 12.0  | 900  | 0.6010          | 0.8533   |
| 0.1021        | 13.0  | 975  | 0.6798          | 0.8533   |
| 0.0647        | 14.0  | 1050 | 0.7265          | 0.8567   |
| 0.0502        | 15.0  | 1125 | 0.6910          | 0.8667   |
| 0.0326        | 16.0  | 1200 | 0.7374          | 0.8667   |
| 0.0554        | 17.0  | 1275 | 0.7250          | 0.8567   |
| 0.0312        | 18.0  | 1350 | 0.7943          | 0.8567   |
| 0.0729        | 19.0  | 1425 | 0.7315          | 0.86     |
| 0.0562        | 20.0  | 1500 | 0.7602          | 0.8533   |


### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3

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

wav2vec2-finetuned-on-shEMO
===========================


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: 1.0218
* Accuracy: 0.8


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: 3e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 4
* total\_train\_batch\_size: 32
* 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


### Training results



### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.11.0
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 3e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 4
* total\_train\_batch\_size: 32
* 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 ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.11.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #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: 3e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 4
* total\_train\_batch\_size: 32
* 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 ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.11.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #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: 3e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 4
* total\_train\_batch\_size: 32
* 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### Training results### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.11.0
* Tokenizers 0.13.3