wav2vec2-xls-r-300m-intent-classification-ori

This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the None dataset. It achieves the following results on the evaluation set:

• Loss: 1.3107
• Accuracy: 0.625

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: 3e-05
• train_batch_size: 2
• eval_batch_size: 2
• seed: 42
• gradient_accumulation_steps: 4
• total_train_batch_size: 8
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_ratio: 0.1
• num_epochs: 45

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
2.1982	1.0	14	2.1951	0.0625
2.2021	2.0	28	2.1847	0.1458
2.1819	3.0	42	2.1661	0.3333
2.1789	4.0	56	2.1413	0.3333
2.164	5.0	70	2.1183	0.3333
2.1484	6.0	84	2.0974	0.3333
2.1199	7.0	98	2.0939	0.3333
2.1343	8.0	112	2.0829	0.3333
2.1397	9.0	126	2.0654	0.3333
2.1045	10.0	140	2.0553	0.3333
2.1083	11.0	154	2.0255	0.3333
2.0914	12.0	168	2.0065	0.3333
2.0434	13.0	182	1.9696	0.3333
2.0687	14.0	196	1.9231	0.4167
2.0237	15.0	210	1.8679	0.4167
1.9562	16.0	224	1.8184	0.4167
2.0361	17.0	238	1.8803	0.3958
1.888	18.0	252	1.7802	0.4167
1.899	19.0	266	1.7662	0.4167
1.8959	20.0	280	1.7076	0.4167
1.8368	21.0	294	1.6566	0.4375
1.7358	22.0	308	1.6283	0.5
1.7877	23.0	322	1.6411	0.4583
1.7311	24.0	336	1.5525	0.5208
1.7079	25.0	350	1.5163	0.5
1.6496	26.0	364	1.5458	0.5
1.6374	27.0	378	1.5211	0.5
1.6048	28.0	392	1.4533	0.5417
1.5927	29.0	406	1.4319	0.5
1.4987	30.0	420	1.4579	0.5208
1.5745	31.0	434	1.4167	0.6042
1.4632	32.0	448	1.4471	0.5417
1.4686	33.0	462	1.4116	0.5625
1.5368	34.0	476	1.3872	0.6042
1.4327	35.0	490	1.3491	0.5833
1.3978	36.0	504	1.3325	0.5833
1.4509	37.0	518	1.3236	0.6042
1.3881	38.0	532	1.3426	0.5833
1.39	39.0	546	1.3137	0.6042
1.4153	40.0	560	1.3123	0.625
1.3635	41.0	574	1.3224	0.6042
1.403	42.0	588	1.3111	0.6042
1.3763	43.0	602	1.3197	0.5833
1.3539	44.0	616	1.3077	0.6042
1.306	45.0	630	1.3107	0.625

Framework versions

• Transformers 4.20.1
• Pytorch 1.11.0
• Datasets 2.1.0
• Tokenizers 0.12.1