wav2vec-base-crema-sentiment-analysis

Supreeta03/wav2vec-base-crema-sentiment-analysis

wav2vec-base-crema-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 8, 2024
Updated: Apr 10, 2024
SHA: f95355a7

Base models

facebook/wav2vec2-base

Datasets

Supreeta03/CREMA-audioData

Model card

From the Hugging Face model README

wav2vec-base-CREMA-sentiment-analysis

This model is a fine-tuned version of facebook/wav2vec2-base on an .Supreeta03/CREMA-audioData. It achieves the following results on the evaluation set:

Loss: 1.3834
Accuracy: 0.5756

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: 5e-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: cosine
lr_scheduler_warmup_ratio: 0.1
num_epochs: 50

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
1.7533	0.99	37	1.7438	0.3056
1.5942	1.99	74	1.5781	0.3409
1.4434	2.98	111	1.5167	0.3568
1.4327	4.0	149	1.4241	0.4156
1.3499	4.99	186	1.3148	0.4819
1.2126	5.99	223	1.2915	0.4887
1.1838	6.98	260	1.2672	0.4971
1.1141	8.0	298	1.2433	0.5046
1.1163	8.99	335	1.1968	0.5281
1.0099	9.99	372	1.1610	0.5516
0.9566	10.98	409	1.1547	0.5567
0.906	12.0	447	1.1565	0.5584
0.8275	12.99	484	1.1442	0.5718
0.7813	13.99	521	1.2570	0.5550
0.711	14.98	558	1.1654	0.5567
0.7146	16.0	596	1.4391	0.5323
0.6597	16.99	633	1.2309	0.5659
0.5579	17.99	670	1.2385	0.5760
0.5874	18.98	707	1.2609	0.5760
0.4905	20.0	745	1.3433	0.5777
0.5089	20.99	782	1.3727	0.5584
0.4414	21.99	819	1.3488	0.5676
0.3837	22.98	856	1.3572	0.5819
0.4419	24.0	894	1.5063	0.5651
0.387	24.99	931	1.4656	0.5659
0.4068	25.99	968	1.5354	0.5701
0.3496	26.98	1005	1.4607	0.5684
0.3579	28.0	1043	1.5049	0.5651
0.3135	28.99	1080	1.4441	0.5743
0.3612	29.99	1117	1.5329	0.5701
0.2599	30.98	1154	1.5920	0.5668
0.2517	32.0	1192	1.5633	0.5626
0.2439	32.99	1229	1.5979	0.5718
0.2891	33.99	1266	1.5590	0.5785
0.2564	34.98	1303	1.5978	0.5751
0.2132	36.0	1341	1.6400	0.5634
0.1882	36.99	1378	1.6309	0.5718
0.2027	37.99	1415	1.6376	0.5743
0.2555	38.98	1452	1.7064	0.5693
0.1872	40.0	1490	1.6575	0.5819
0.1891	40.99	1527	1.6606	0.5735
0.1795	41.99	1564	1.6507	0.5735
0.1931	42.98	1601	1.6627	0.5760
0.1574	44.0	1639	1.6944	0.5802
0.1842	44.99	1676	1.7082	0.5768
0.1859	45.99	1713	1.7004	0.5768
0.2088	46.98	1750	1.7002	0.5802
0.197	48.0	1788	1.6969	0.5751
0.1902	48.99	1825	1.6996	0.5743
0.1771	49.66	1850	1.6998	0.5743

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 8, 2024
Updated: Apr 10, 2024