Wav2Vec2_EmoRecog_Model_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: 1.8440
  • Accuracy: 0.4349

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: 2e-05
  • train_batch_size: 16
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: linear
  • num_epochs: 20

Training results

Training Loss Epoch Step Validation Loss Accuracy
1.7698 1.0 377 1.6608 0.3513
1.6102 2.0 754 1.6074 0.3625
1.5556 3.0 1131 1.5894 0.3778
1.4899 4.0 1508 1.5643 0.3858
1.4322 5.0 1885 1.5250 0.4084
1.3737 6.0 2262 1.5445 0.4110
1.3217 7.0 2639 1.5287 0.4210
1.2686 8.0 3016 1.5635 0.4243
1.1999 9.0 3393 1.5674 0.4223
1.1511 10.0 3770 1.5881 0.4363
1.087 11.0 4147 1.6162 0.4177
1.0309 12.0 4524 1.6487 0.4296
0.9778 13.0 4901 1.7363 0.4210
0.9344 14.0 5278 1.7568 0.4210
0.9108 15.0 5655 1.7051 0.4416
0.8449 16.0 6032 1.7945 0.4329
0.8268 17.0 6409 1.7778 0.4402
0.7991 18.0 6786 1.7972 0.4382
0.7604 19.0 7163 1.8238 0.4276
0.7329 20.0 7540 1.8440 0.4349

Framework versions

  • Transformers 4.47.1
  • Pytorch 2.5.1+cu121
  • Datasets 3.2.0
  • Tokenizers 0.21.0
Downloads last month
6
Safetensors
Model size
94.6M params
Tensor type
F32
·
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Model tree for yenrong/Wav2Vec2_EmoRecog_Model_v2

Finetuned
(693)
this model