humor_model_v1 – AI Model by rishiA | AlphaNeural AI

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rishiA/
humor_model_v1

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audio-classification

generated_from_trainer

facebook/wav2vec2-base

endpoints_compatible

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humor_model_v1

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: 0.1840
Accuracy: 0.9231

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: 32
eval_batch_size: 32
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 128
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	0.9231	6	0.5754	0.9231
0.5907	2.0	13	0.3002	0.9231
0.5907	2.9231	19	0.2467	0.9231
0.3341	4.0	26	0.2232	0.9231
0.2424	4.9231	32	0.2288	0.8894
0.2424	6.0	39	0.2577	0.8510
0.1678	6.9231	45	0.2725	0.8558
0.1293	8.0	52	0.2767	0.8606
0.1293	8.9231	58	0.1823	0.9279
0.1149	9.2308	60	0.1840	0.9231

Framework versions

Transformers 4.41.1
Pytorch 2.3.0+cu121
Datasets 2.19.1
Tokenizers 0.19.1