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# finetuned_wav2vec2.0-base-on-IEMOCAP_3

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: 1.3119
- Accuracy: 0.6412

## 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: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.197         | 1.0   | 109  | 1.1517          | 0.4738   |
| 0.9312        | 2.0   | 219  | 0.9722          | 0.5774   |
| 0.8183        | 3.0   | 328  | 0.8322          | 0.6640   |
| 0.7456        | 4.0   | 438  | 0.7201          | 0.7198   |
| 0.599         | 5.0   | 547  | 0.7853          | 0.7118   |
| 0.4166        | 6.0   | 657  | 0.6359          | 0.7711   |
| 0.2507        | 7.0   | 766  | 0.7845          | 0.7415   |
| 0.2794        | 8.0   | 876  | 0.8188          | 0.7494   |
| 0.1777        | 9.0   | 985  | 0.7406          | 0.7950   |
| 0.1344        | 10.0  | 1095 | 0.8735          | 0.7620   |
| 0.0719        | 11.0  | 1204 | 0.9456          | 0.7688   |
| 0.0577        | 12.0  | 1314 | 0.9727          | 0.7768   |
| 0.0405        | 13.0  | 1423 | 1.0440          | 0.7756   |
| 0.0619        | 14.0  | 1533 | 1.0239          | 0.7813   |
| 0.0299        | 14.93 | 1635 | 1.0343          | 0.7790   |


### Framework versions

- Transformers 4.29.2
- Pytorch 2.0.0
- Datasets 2.12.0
- Tokenizers 0.13.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "model-index": [{"name": "finetuned_wav2vec2.0-base-on-IEMOCAP_3", "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 

finetuned\_wav2vec2.0-base-on-IEMOCAP\_3
========================================


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: 1.3119
* Accuracy: 0.6412


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: 15


### Training results



### Framework versions


* Transformers 4.29.2
* Pytorch 2.0.0
* Datasets 2.12.0
* 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: 15 ### Training results ### Framework versions


* Transformers 4.29.2
* Pytorch 2.0.0
* Datasets 2.12.0
* 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: 15 ### Training results ### Framework versions


* Transformers 4.29.2
* Pytorch 2.0.0
* Datasets 2.12.0
* Tokenizers 0.13.3