minoosh's picture
update model card README.md
da250ea
metadata
license: apache-2.0
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: finetuned_wav2vec2.0-base-on-IEMOCAP_2
    results: []

finetuned_wav2vec2.0-base-on-IEMOCAP_2

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: 1.1569
  • Accuracy: 0.7390

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
1.1881 0.99 112 1.2005 0.4768
1.0121 2.0 225 1.0271 0.5619
0.8569 3.0 338 0.9382 0.6018
0.8679 4.0 451 0.8015 0.6947
0.5643 4.99 563 0.7752 0.7046
0.4579 6.0 676 0.7699 0.7400
0.3993 7.0 789 0.8323 0.7102
0.319 8.0 902 0.7763 0.7400
0.1876 8.99 1014 0.8912 0.7334
0.1888 10.0 1127 0.8836 0.7312
0.1526 11.0 1240 1.0474 0.7290
0.0451 12.0 1353 1.0455 0.7434
0.1281 12.99 1465 1.1207 0.7412
0.0363 14.0 1578 1.1232 0.7445
0.0512 14.9 1680 1.1217 0.7412

Framework versions

  • Transformers 4.29.2
  • Pytorch 2.0.0
  • Datasets 2.12.0
  • Tokenizers 0.13.3