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# iewav2vec2-finetuned-on-shEMO

This model is a fine-tuned version of [minoosh/wav2vec2-base-finetuned-ie](https://huggingface.co/minoosh/wav2vec2-base-finetuned-ie) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9088
- Accuracy: 0.82

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.0779        | 1.0   | 75   | 0.9736          | 0.7133   |
| 0.7753        | 2.0   | 150  | 0.7869          | 0.7467   |
| 0.5784        | 3.0   | 225  | 0.6579          | 0.7867   |
| 0.5088        | 4.0   | 300  | 0.6393          | 0.7933   |
| 0.4454        | 5.0   | 375  | 0.6090          | 0.83     |
| 0.3197        | 6.0   | 450  | 0.7735          | 0.8067   |
| 0.235         | 7.0   | 525  | 0.6943          | 0.8333   |
| 0.1648        | 8.0   | 600  | 0.6958          | 0.8367   |
| 0.1016        | 9.0   | 675  | 0.7437          | 0.8333   |
| 0.0822        | 10.0  | 750  | 0.6435          | 0.8467   |
| 0.1434        | 11.0  | 825  | 0.6448          | 0.86     |
| 0.0748        | 12.0  | 900  | 0.7208          | 0.86     |
| 0.0403        | 13.0  | 975  | 0.6549          | 0.8733   |
| 0.0365        | 14.0  | 1050 | 0.7136          | 0.8667   |
| 0.0249        | 15.0  | 1125 | 0.6958          | 0.87     |
| 0.0462        | 16.0  | 1200 | 0.8340          | 0.8533   |
| 0.0061        | 17.0  | 1275 | 0.8503          | 0.84     |
| 0.0257        | 18.0  | 1350 | 0.9144          | 0.85     |
| 0.0262        | 19.0  | 1425 | 0.8671          | 0.8567   |
| 0.005         | 20.0  | 1500 | 0.8572          | 0.8567   |


### 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": "iewav2vec2-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 

iewav2vec2-finetuned-on-shEMO
=============================


This model is a fine-tuned version of minoosh/wav2vec2-base-finetuned-ie on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 0.9088
* Accuracy: 0.82


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