wav2vec2-base-CREMAD-sentiment-analysis

Supreeta03/wav2vec2-base-CREMAD-sentiment-analysis

wav2vec2-base-CREMAD-sentiment-analysis is a audio classification model from Supreeta03. Use it for the audio classification task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as apache-2.0.

should probably proofread and complete it, then remove this comment. --

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At a glance

Task: Audio Classification
Library: transformers
License: apache-2.0
Model type: wav2vec2
Access: Public
Created: Apr 18, 2024
Updated: Apr 18, 2024
SHA: 8c87d3b5

Base models

facebook/wav2vec2-base

Model card

From the Hugging Face model README

wav2vec-best-CREMA-sentiment-analysis

This model is a fine-tuned version of facebook/wav2vec2-base on an unknown dataset. It achieves the following results on the evaluation set:

Top2 Accuracy: 0.8940
Loss: 0.8287
Accuracy: 0.7074

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: 1e-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: 30

Training results

Training Loss	Epoch	Step	Top2 Accuracy	Validation Loss	Accuracy
1.7824	0.98	43	0.4982	1.7749	0.2482
1.7115	1.99	87	0.5466	1.6566	0.3638
1.5255	2.99	131	0.6604	1.5017	0.4418
1.3716	4.0	175	0.7679	1.3359	0.5636
1.2436	4.98	218	0.8271	1.1862	0.6407
1.1366	5.99	262	0.8315	1.1223	0.6595
1.0322	6.99	306	0.8593	1.0422	0.6747
0.9668	8.0	350	0.8907	0.9335	0.7222
0.8932	8.98	393	0.8943	0.9093	0.7231
0.8431	9.99	437	0.8692	0.9163	0.7115
0.8047	10.99	481	0.8996	0.8488	0.7375
0.7444	12.0	525	0.8898	0.8611	0.7204
0.6921	12.98	568	0.8916	0.8399	0.7258
0.6973	13.99	612	0.8844	0.8425	0.7231
0.632	14.99	656	0.8880	0.8308	0.7249
0.6275	16.0	700	0.8862	0.8400	0.7177
0.6153	16.98	743	0.8934	0.8266	0.7330
0.5597	17.99	787	0.8934	0.8157	0.7357
0.5658	18.99	831	0.8862	0.8015	0.7446
0.54	20.0	875	0.8943	0.8368	0.7258
0.5301	20.98	918	0.9023	0.8095	0.7321
0.5262	21.99	962	0.8817	0.8521	0.7168
0.4754	22.99	1006	0.8987	0.8003	0.7428
0.4753	24.0	1050	0.8952	0.7988	0.7410
0.455	24.98	1093	0.8952	0.7902	0.7419
0.4574	25.99	1137	0.8871	0.8030	0.7366
0.4618	26.99	1181	0.8970	0.8051	0.7294
0.4222	28.0	1225	0.8925	0.8108	0.7267
0.4301	28.98	1268	0.8934	0.8066	0.7339
0.4147	29.49	1290	0.8916	0.8072	0.7357

Framework versions

Transformers 4.38.2
Pytorch 2.2.1+cu121
Datasets 2.18.0
Tokenizers 0.15.2

Task: Audio Classification
Library: transformers
Type: wav2vec2
License: apache-2.0
Created: Apr 18, 2024
Updated: Apr 18, 2024