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metadata
license: apache-2.0
library_name: peft
tags:
  - generated_from_trainer
base_model: openai/whisper-large-v3
model-index:
  - name: whisper-large-v3-MH-fine-tuned
    results: []

whisper-large-v3-MH-fine-tuned

This model is a fine-tuned version of openai/whisper-large-v3 on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 1.1026

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: 0.001
  • train_batch_size: 10
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 50
  • num_epochs: 100
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss
No log 1.0 1 1.6433
No log 2.0 2 1.6256
No log 3.0 3 1.5850
No log 4.0 4 1.5268
No log 5.0 5 1.4583
No log 6.0 6 1.3911
No log 7.0 7 1.3293
No log 8.0 8 1.2727
No log 9.0 9 1.2201
No log 10.0 10 1.1695
No log 11.0 11 1.1209
No log 12.0 12 1.0779
No log 13.0 13 1.0471
No log 14.0 14 1.0264
No log 15.0 15 1.0034
No log 16.0 16 0.9841
No log 17.0 17 0.9749
No log 18.0 18 0.9693
No log 19.0 19 0.9609
No log 20.0 20 0.9441
No log 21.0 21 0.9278
No log 22.0 22 0.9189
No log 23.0 23 0.9244
No log 24.0 24 0.9232
0.9846 25.0 25 0.9187
0.9846 26.0 26 0.9295
0.9846 27.0 27 0.9583
0.9846 28.0 28 0.9774
0.9846 29.0 29 0.9789
0.9846 30.0 30 0.9960
0.9846 31.0 31 1.0306
0.9846 32.0 32 1.0483
0.9846 33.0 33 1.0384
0.9846 34.0 34 1.0458
0.9846 35.0 35 1.0651
0.9846 36.0 36 1.0418
0.9846 37.0 37 1.0329
0.9846 38.0 38 1.0425
0.9846 39.0 39 1.0538
0.9846 40.0 40 1.0397
0.9846 41.0 41 1.0374
0.9846 42.0 42 1.0477
0.9846 43.0 43 1.0589
0.9846 44.0 44 1.0609
0.9846 45.0 45 1.0615
0.9846 46.0 46 1.0700
0.9846 47.0 47 1.0893
0.9846 48.0 48 1.0948
0.9846 49.0 49 1.0906
0.2714 50.0 50 1.1002
0.2714 51.0 51 1.1112
0.2714 52.0 52 1.1162
0.2714 53.0 53 1.1117
0.2714 54.0 54 1.1243
0.2714 55.0 55 1.1166
0.2714 56.0 56 1.1230
0.2714 57.0 57 1.1156
0.2714 58.0 58 1.1162
0.2714 59.0 59 1.1310
0.2714 60.0 60 1.0921
0.2714 61.0 61 1.1188
0.2714 62.0 62 1.0336
0.2714 63.0 63 0.9937
0.2714 64.0 64 1.0263
0.2714 65.0 65 1.0224
0.2714 66.0 66 1.0067
0.2714 67.0 67 1.0112
0.2714 68.0 68 1.0143
0.2714 69.0 69 1.0155
0.2714 70.0 70 1.0211
0.2714 71.0 71 1.0260
0.2714 72.0 72 1.0292
0.2714 73.0 73 1.0363
0.2714 74.0 74 1.0443
0.2554 75.0 75 1.0529
0.2554 76.0 76 1.0624
0.2554 77.0 77 1.0681
0.2554 78.0 78 1.0688
0.2554 79.0 79 1.0684
0.2554 80.0 80 1.0690
0.2554 81.0 81 1.0702
0.2554 82.0 82 1.0719
0.2554 83.0 83 1.0748
0.2554 84.0 84 1.0789
0.2554 85.0 85 1.0826
0.2554 86.0 86 1.0848
0.2554 87.0 87 1.0865
0.2554 88.0 88 1.0876
0.2554 89.0 89 1.0887
0.2554 90.0 90 1.0898
0.2554 91.0 91 1.0915
0.2554 92.0 92 1.0934
0.2554 93.0 93 1.0956
0.2554 94.0 94 1.0978
0.2554 95.0 95 1.0997
0.2554 96.0 96 1.1010
0.2554 97.0 97 1.1018
0.2554 98.0 98 1.1023
0.2554 99.0 99 1.1025
0.2451 100.0 100 1.1026

Framework versions

  • PEFT 0.11.1.dev0
  • Transformers 4.40.2
  • Pytorch 2.2.1+cu121
  • Datasets 2.19.1
  • Tokenizers 0.19.1