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metadata
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: wav2vec2-base-finetuned-ravdess
    results: []

wav2vec2-base-finetuned-ravdess

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: 0.8783
  • Accuracy: 0.7535

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: 32
  • eval_batch_size: 32
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 128
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 50

Training results

Training Loss Epoch Step Validation Loss Accuracy
No log 1.0 9 2.0739 0.1562
2.0781 2.0 18 2.0611 0.1181
2.0668 3.0 27 2.0308 0.2535
2.0429 4.0 36 1.9606 0.2604
1.974 5.0 45 1.8449 0.2847
1.8594 6.0 54 1.7678 0.2917
1.7675 7.0 63 1.7700 0.2708
1.6932 8.0 72 1.6049 0.3889
1.5656 9.0 81 1.5510 0.4444
1.4658 10.0 90 1.4535 0.4583
1.4658 11.0 99 1.4101 0.4514
1.3843 12.0 108 1.3687 0.5
1.3085 13.0 117 1.3333 0.5035
1.2264 14.0 126 1.3208 0.5208
1.1349 15.0 135 1.3048 0.5312
1.0861 16.0 144 1.2428 0.5799
0.9836 17.0 153 1.1886 0.5799
0.9273 18.0 162 1.1574 0.6146
0.8686 19.0 171 1.1356 0.6111
0.814 20.0 180 1.1261 0.6285
0.814 21.0 189 1.0796 0.6007
0.7279 22.0 198 1.0277 0.6493
0.6845 23.0 207 1.0408 0.6840
0.6283 24.0 216 0.9708 0.7153
0.5835 25.0 225 0.9926 0.6875
0.5445 26.0 234 1.0126 0.6840
0.497 27.0 243 0.9502 0.6979
0.4508 28.0 252 0.9432 0.7118
0.4331 29.0 261 0.9246 0.7014
0.4023 30.0 270 0.9649 0.6875
0.4023 31.0 279 0.9114 0.7049
0.3924 32.0 288 0.9460 0.7118
0.3797 33.0 297 0.9605 0.7118
0.3494 34.0 306 0.8505 0.7396
0.3195 35.0 315 0.8830 0.7188
0.3148 36.0 324 0.9352 0.7014
0.2856 37.0 333 0.8551 0.7292
0.2831 38.0 342 0.8505 0.7326
0.2718 39.0 351 0.8800 0.7396
0.2624 40.0 360 0.8991 0.7153
0.2624 41.0 369 0.8724 0.7465
0.2612 42.0 378 0.9138 0.7049
0.2511 43.0 387 0.8914 0.7257
0.2324 44.0 396 0.8783 0.7535
0.2228 45.0 405 0.9215 0.7188
0.2244 46.0 414 0.8904 0.7431
0.2192 47.0 423 0.9142 0.7326
0.217 48.0 432 0.8891 0.7361
0.2146 49.0 441 0.9009 0.7326
0.215 50.0 450 0.8994 0.7361

Framework versions

  • Transformers 4.31.0
  • Pytorch 2.0.1+cu118
  • Datasets 2.14.4
  • Tokenizers 0.13.3