Supreeta03/wav2vec2-base-sentiment-analysis-CREMA

wav2vec-best-CREMA-sentiment-analysis-best3

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

• top2 Accuracy: 0.7824
• Loss: 1.1563
• Accuracy: 0.5601

Model description

Fine tuned from [facebook/wav2vec2-base] for performing sentiment analysis on audio data.

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: 20

Training results

Training Loss	Epoch	Step	Top2 Accuracy	Validation Loss	Accuracy
1.7555	0.99	37	0.5281	1.7048	0.2905
1.5612	1.99	74	0.5819	1.5406	0.3493
1.4333	2.98	111	0.6373	1.4668	0.3778
1.3933	4.0	149	0.6809	1.3798	0.4450
1.3418	4.99	186	0.7045	1.3120	0.4719
1.2238	5.99	223	0.7263	1.2718	0.4979
1.1896	6.98	260	0.7313	1.2430	0.5113
1.1501	8.0	298	0.7296	1.2631	0.5088
1.1052	8.99	335	0.7506	1.2462	0.5097
1.068	9.99	372	0.7641	1.1822	0.5399
1.0594	10.98	409	0.7590	1.1700	0.5575
0.9519	12.0	447	0.7733	1.1465	0.5516
0.9513	12.99	484	0.7918	1.1428	0.5676
0.9324	13.99	521	0.7666	1.1721	0.5634
0.9173	14.98	558	0.7825	1.1494	0.5584
0.8781	16.0	596	0.7918	1.1468	0.5718
0.8627	16.99	633	0.7775	1.1554	0.5575
0.83	17.99	670	0.7817	1.1438	0.5718
0.8305	18.98	707	0.7935	1.1323	0.5760
0.8314	19.87	740	0.7851	1.1341	0.5726

Framework versions

• Transformers 4.38.2
• Pytorch 2.2.1+cu121
• Datasets 2.18.0
• Tokenizers 0.15.2