wav2vec2-base-intent-classification-ori

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

• Loss: 0.4928
• Accuracy: 0.9167

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: 1
• eval_batch_size: 1
• seed: 42
• gradient_accumulation_steps: 4
• total_train_batch_size: 4
• 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
2.1867	1.0	28	2.1745	0.2708
2.1177	2.0	56	2.1165	0.2708
2.1012	3.0	84	2.0553	0.2708
1.9851	4.0	112	1.9551	0.375
1.9092	5.0	140	1.9765	0.2917
1.6848	6.0	168	1.8461	0.2917
1.6576	7.0	196	1.5223	0.5
1.4492	8.0	224	1.4500	0.4792
1.2193	9.0	252	1.5349	0.4792
1.1149	10.0	280	1.2159	0.5833
1.0615	11.0	308	1.1469	0.6875
1.0584	12.0	336	1.2778	0.6042
0.8237	13.0	364	1.1774	0.5625
0.6699	14.0	392	0.9661	0.6875
0.7414	15.0	420	1.2787	0.5208
0.5324	16.0	448	0.8592	0.7292
0.3753	17.0	476	0.6860	0.7917
0.3274	18.0	504	0.6210	0.8333
0.3667	19.0	532	0.7310	0.75
0.2347	20.0	560	0.6801	0.7292
0.2036	21.0	588	0.9876	0.6875
0.1711	22.0	616	0.6323	0.7917
0.205	23.0	644	0.4414	0.8958
0.0892	24.0	672	0.4253	0.8958
0.0777	25.0	700	0.4703	0.8958
0.0717	26.0	728	0.4883	0.8958
0.041	27.0	756	0.6224	0.8542
0.0493	28.0	784	0.5839	0.875
0.0405	29.0	812	0.6454	0.8542
0.04	30.0	840	0.6102	0.875
0.0333	31.0	868	0.6080	0.875
0.0303	32.0	896	0.5539	0.875
0.025	33.0	924	0.5799	0.8958
0.0246	34.0	952	0.5766	0.8958
0.0209	35.0	980	0.5700	0.8958
0.0225	36.0	1008	0.5709	0.8958
0.0225	37.0	1036	0.5582	0.8958
0.0217	38.0	1064	0.5258	0.875
0.0207	39.0	1092	0.5058	0.8958
0.0234	40.0	1120	0.4981	0.8958
0.021	41.0	1148	0.4928	0.9167
0.0224	42.0	1176	0.4962	0.9167
0.0212	43.0	1204	0.5329	0.8958
0.0208	44.0	1232	0.5727	0.8958
0.0206	45.0	1260	0.5733	0.8958

Framework versions

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