wav2vec2-base-finetuned-sentiment-mesd-v2

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

• Loss: 1.7213
• Accuracy: 0.3923

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 1.25e-05
• train_batch_size: 64
• eval_batch_size: 40
• seed: 42
• gradient_accumulation_steps: 4
• total_train_batch_size: 256
• 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	Validation Loss	Accuracy
No log	0.86	3	1.7961	0.1462
1.9685	1.86	6	1.7932	0.1692
1.9685	2.86	9	1.7891	0.2
2.1386	3.86	12	1.7820	0.2923
1.9492	4.86	15	1.7750	0.2923
1.9492	5.86	18	1.7684	0.2846
2.1143	6.86	21	1.7624	0.3231
2.1143	7.86	24	1.7561	0.3308
2.0945	8.86	27	1.7500	0.3462
1.9121	9.86	30	1.7443	0.3385
1.9121	10.86	33	1.7386	0.3231
2.0682	11.86	36	1.7328	0.3231
2.0682	12.86	39	1.7272	0.3769
2.0527	13.86	42	1.7213	0.3923
1.8705	14.86	45	1.7154	0.3846
1.8705	15.86	48	1.7112	0.3846
2.0263	16.86	51	1.7082	0.3769
2.0263	17.86	54	1.7044	0.3846
2.0136	18.86	57	1.7021	0.3846
1.8429	19.86	60	1.7013	0.3846

Framework versions

• Transformers 4.17.0
• Pytorch 1.10.0+cu111
• Datasets 2.0.0
• Tokenizers 0.11.6