Edit model card

wav2vec2-base-finetuned-iemocap-fin2

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

  • Loss: 1.1912
  • Accuracy: 0.5597
  • F1: 0.5453

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: 8
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 32
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 15

Training results

Training Loss Epoch Step Validation Loss Accuracy F1
1.2603 1.0 102 1.2581 0.4617 0.4105
1.1338 2.0 204 1.1471 0.4801 0.4369
1.0899 3.0 306 1.1386 0.4782 0.4459
1.0501 4.0 408 1.0894 0.5218 0.5096
0.9892 5.0 510 1.0778 0.5422 0.5339
0.8943 6.0 612 1.1394 0.5141 0.4730
0.9112 7.0 714 1.0634 0.5529 0.5379
0.8688 8.0 816 1.0726 0.5664 0.5576
0.8807 9.0 918 1.2264 0.5209 0.4822
0.8027 10.0 1020 1.0469 0.5839 0.5843
0.7069 11.0 1122 1.1171 0.5587 0.5398
0.6508 12.0 1224 1.1889 0.5480 0.5292
0.6406 13.0 1326 1.1800 0.5664 0.5501
0.6072 14.0 1428 1.1841 0.5558 0.5413
0.6277 15.0 1530 1.1912 0.5597 0.5453

Framework versions

  • Transformers 4.34.0
  • Pytorch 2.0.1+cu118
  • Datasets 2.14.5
  • Tokenizers 0.14.0
Downloads last month
12
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 Zahra99/wav2vec2-base-finetuned-iemocap-fin2

Finetuned
(649)
this model