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# ASTie-finetuned-on-shEMO

This model is a fine-tuned version of [minoosh/ast-finetuned-audioset-10-10-0.4593-finetuned-ie](https://huggingface.co/minoosh/ast-finetuned-audioset-10-10-0.4593-finetuned-ie) on the None dataset.
It achieves the following results on the evaluation set:
- eval_loss: 1.4229
- eval_accuracy: 0.8167
- eval_runtime: 37.6165
- eval_samples_per_second: 7.975
- eval_steps_per_second: 1.01
- epoch: 16.36
- step: 1227

## 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: 30

### Framework versions

- Transformers 4.27.4
- Pytorch 1.13.0
- Datasets 2.11.0
- Tokenizers 0.13.2

{"license": "bsd-3-clause", "tags": ["generated_from_trainer"], "model-index": [{"name": "ASTie-finetuned-on-shEMO", "results": []}]}
transformers pytorch audio-spectrogram-transformer audio-classification generated_from_trainer license:bsd-3-clause endpoints_compatible region:us
TAGS
#transformers #pytorch #audio-spectrogram-transformer #audio-classification #generated_from_trainer #license-bsd-3-clause #endpoints_compatible #region-us 




# ASTie-finetuned-on-shEMO

This model is a fine-tuned version of minoosh/ast-finetuned-audioset-10-10-0.4593-finetuned-ie on the None dataset.
It achieves the following results on the evaluation set:
- eval_loss: 1.4229
- eval_accuracy: 0.8167
- eval_runtime: 37.6165
- eval_samples_per_second: 7.975
- eval_steps_per_second: 1.01
- epoch: 16.36
- step: 1227

## 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: 30

### Framework versions

- Transformers 4.27.4
- Pytorch 1.13.0
- Datasets 2.11.0
- Tokenizers 0.13.2

# ASTie-finetuned-on-shEMO

This model is a fine-tuned version of minoosh/ast-finetuned-audioset-10-10-0.4593-finetuned-ie on the None dataset.
It achieves the following results on the evaluation set:
- eval_loss: 1.4229
- eval_accuracy: 0.8167
- eval_runtime: 37.6165
- eval_samples_per_second: 7.975
- eval_steps_per_second: 1.01
- epoch: 16.36
- step: 1227 ## 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: 30 ### Framework versions

- Transformers 4.27.4
- Pytorch 1.13.0
- Datasets 2.11.0
- Tokenizers 0.13.2
TAGS
#transformers #pytorch #audio-spectrogram-transformer #audio-classification #generated_from_trainer #license-bsd-3-clause #endpoints_compatible #region-us 
 # ASTie-finetuned-on-shEMO

This model is a fine-tuned version of minoosh/ast-finetuned-audioset-10-10-0.4593-finetuned-ie on the None dataset.
It achieves the following results on the evaluation set:
- eval_loss: 1.4229
- eval_accuracy: 0.8167
- eval_runtime: 37.6165
- eval_samples_per_second: 7.975
- eval_steps_per_second: 1.01
- epoch: 16.36
- step: 1227 ## 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: 30 ### Framework versions

- Transformers 4.27.4
- Pytorch 1.13.0
- Datasets 2.11.0
- Tokenizers 0.13.2
TAGS
#transformers #pytorch #audio-spectrogram-transformer #audio-classification #generated_from_trainer #license-bsd-3-clause #endpoints_compatible #region-us 
# ASTie-finetuned-on-shEMO

This model is a fine-tuned version of minoosh/ast-finetuned-audioset-10-10-0.4593-finetuned-ie on the None dataset.
It achieves the following results on the evaluation set:
- eval_loss: 1.4229
- eval_accuracy: 0.8167
- eval_runtime: 37.6165
- eval_samples_per_second: 7.975
- eval_steps_per_second: 1.01
- epoch: 16.36
- step: 1227## 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: 30### Framework versions

- Transformers 4.27.4
- Pytorch 1.13.0
- Datasets 2.11.0
- Tokenizers 0.13.2