wav2vec2-base-finetuned-sentiment-mesd-v2 – AI Model by DrishtiSharma | AlphaNeural AI

You can deploy this model and start earning money today!

DrishtiSharma/
wav2vec2-base-finetuned-sentiment-mesd-v2

like

0

audio-classification

generated_from_trainer

endpoints_compatible

Views

No views yet

wav2vec2-base-finetuned-sentiment-mesd-v2

This model is a fine-tuned version of facebook/wav2vec2-base on the None dataset. It achieves the following results on the evaluation set:

Loss: 1.7213
Accuracy: 0.3923

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 1.25e-05
train_batch_size: 64
eval_batch_size: 40
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 256
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 20

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	0.86	3	1.7961	0.1462
1.9685	1.86	6	1.7932	0.1692
1.9685	2.86	9	1.7891	0.2
2.1386	3.86	12	1.7820	0.2923
1.9492	4.86	15	1.7750	0.2923
1.9492	5.86	18	1.7684	0.2846
2.1143	6.86	21	1.7624	0.3231
2.1143	7.86	24	1.7561	0.3308
2.0945	8.86	27	1.7500	0.3462
1.9121	9.86	30	1.7443	0.3385
1.9121	10.86	33	1.7386	0.3231
2.0682	11.86	36	1.7328	0.3231
2.0682	12.86	39	1.7272	0.3769
2.0527	13.86	42	1.7213	0.3923
1.8705	14.86	45	1.7154	0.3846
1.8705	15.86	48	1.7112	0.3846
2.0263	16.86	51	1.7082	0.3769
2.0263	17.86	54	1.7044	0.3846
2.0136	18.86	57	1.7021	0.3846
1.8429	19.86	60	1.7013	0.3846

Framework versions

Transformers 4.17.0
Pytorch 1.10.0+cu111
Datasets 2.0.0
Tokenizers 0.11.6