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Evan-Lin/
trainer

Name: trainer
Rating: 2.5 (5 reviews)

transformers

pytorch

audio-spectrogram-transformer

audio-classification

generated_from_trainer

bsd-3-clause

endpoints_compatible

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trainer

This model is a fine-tuned version of MIT/ast-finetuned-audioset-10-10-0.4593 on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.3684
Accuracy: 0.9275

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: 0.0001
train_batch_size: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 64
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 50
training_steps: 1000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
4.2624	2.0	50	0.3928	0.88
0.9069	4.0	100	0.3259	0.9025
0.9069	6.0	150	0.2775	0.93
0.0567	8.0	200	0.3220	0.9075
0.0567	10.0	250	0.3196	0.9075
0.0109	12.0	300	0.3644	0.9175
0.0109	14.0	350	0.3501	0.93
0.0138	16.0	400	0.3569	0.9275
0.0138	18.0	450	0.3700	0.9225
0.0006	20.0	500	0.3662	0.925
0.0006	22.0	550	0.3669	0.925
0.0002	24.0	600	0.3673	0.925
0.0002	26.0	650	0.3677	0.925
0.0002	28.0	700	0.3679	0.9275
0.0002	30.0	750	0.3680	0.9275
0.0002	32.0	800	0.3681	0.9275
0.0002	34.0	850	0.3684	0.9275
0.0002	36.0	900	0.3683	0.9275
0.0002	38.0	950	0.3684	0.9275
0.0002	40.0	1000	0.3684	0.9275

Framework versions

Transformers 4.27.1
Pytorch 2.0.1+cu117
Datasets 2.13.1
Tokenizers 0.13.3

Evan-Lin/trainer

trainer

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Evan-Lin/
trainer