resultsfinalgerman

This model is a fine-tuned version of padmalcom/wav2vec2-large-emotion-detection-german on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.6302
• Accuracy: 0.6429

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: 4
• eval_batch_size: 4
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 50

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.7053	1.0	13	0.6971	0.3571
0.6994	2.0	26	0.6930	0.5714
0.686	3.0	39	0.6891	0.5714
0.6759	4.0	52	0.6889	0.5714
0.6865	5.0	65	0.6870	0.5714
0.6916	6.0	78	0.6847	0.5714
0.6764	7.0	91	0.6854	0.5714
0.6768	8.0	104	0.6869	0.5714
0.6546	9.0	117	0.6882	0.5714
0.6806	10.0	130	0.6875	0.5714
0.6742	11.0	143	0.6893	0.5714
0.6675	12.0	156	0.6897	0.5714
0.6762	13.0	169	0.6903	0.5714
0.6451	14.0	182	0.6920	0.5714
0.6641	15.0	195	0.6928	0.5714
0.634	16.0	208	0.6974	0.5714
0.6342	17.0	221	0.6983	0.5714
0.6526	18.0	234	0.6992	0.5714
0.6498	19.0	247	0.6926	0.5714
0.6293	20.0	260	0.6842	0.5714
0.5946	21.0	273	0.6833	0.5714
0.6281	22.0	286	0.6761	0.5
0.6084	23.0	299	0.6748	0.5
0.6055	24.0	312	0.6655	0.5
0.5806	25.0	325	0.6670	0.7143
0.62	26.0	338	0.6550	0.5714
0.5741	27.0	351	0.6578	0.7143
0.6261	28.0	364	0.6675	0.6429
0.5069	29.0	377	0.6661	0.6429
0.5526	30.0	390	0.6602	0.6429
0.5145	31.0	403	0.6545	0.6429
0.5634	32.0	416	0.6553	0.6429
0.4619	33.0	429	0.6493	0.6429
0.5694	34.0	442	0.6487	0.6429
0.5045	35.0	455	0.6436	0.6429
0.4623	36.0	468	0.6448	0.6429
0.5001	37.0	481	0.6465	0.6429
0.4779	38.0	494	0.6439	0.6429
0.4751	39.0	507	0.6329	0.6429
0.4426	40.0	520	0.6294	0.6429
0.4341	41.0	533	0.6270	0.6429
0.4282	42.0	546	0.6265	0.6429
0.4908	43.0	559	0.6269	0.6429
0.4073	44.0	572	0.6251	0.6429
0.4207	45.0	585	0.6261	0.6429
0.4757	46.0	598	0.6277	0.6429
0.4357	47.0	611	0.6294	0.6429
0.4473	48.0	624	0.6302	0.6429
0.4047	49.0	637	0.6302	0.6429
0.4881	50.0	650	0.6302	0.6429

Framework versions

• Transformers 4.30.2
• Pytorch 2.0.1+cu118
• Datasets 2.13.1
• Tokenizers 0.13.3