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# finetuned_wav2vec2.0-base-on-IEMOCAP_1

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: 1.6629
- Accuracy: 0.6673

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.2016        | 1.0   | 111  | 1.1443          | 0.5      |
| 1.0629        | 2.0   | 222  | 0.9839          | 0.5830   |
| 0.8111        | 2.99  | 333  | 0.9295          | 0.6233   |
| 0.7455        | 4.0   | 445  | 0.9119          | 0.6570   |
| 0.4654        | 5.0   | 556  | 0.7440          | 0.7186   |
| 0.3648        | 6.0   | 667  | 0.8359          | 0.7007   |
| 0.307         | 6.99  | 778  | 0.7964          | 0.7377   |
| 0.2823        | 8.0   | 890  | 0.8882          | 0.7321   |
| 0.1869        | 9.0   | 1001 | 1.0550          | 0.7186   |
| 0.2022        | 10.0  | 1112 | 1.0110          | 0.7231   |
| 0.0522        | 10.99 | 1223 | 1.1135          | 0.7265   |
| 0.058         | 12.0  | 1335 | 1.1275          | 0.7489   |
| 0.0465        | 13.0  | 1446 | 1.1479          | 0.7545   |
| 0.0321        | 14.0  | 1557 | 1.1885          | 0.7534   |
| 0.0331        | 14.97 | 1665 | 1.2301          | 0.7511   |


### 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_1", "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\_1
========================================


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: 1.6629
* Accuracy: 0.6673


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