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MarathiLORA_test

This model is a fine-tuned version of openai/whisper-small on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3212

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: 0.0001
  • train_batch_size: 8
  • 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
  • training_steps: 3000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss
1.1553 0.2037 100 0.7732
0.6893 0.4073 200 0.6536
0.5571 0.6110 300 0.4662
0.438 0.8147 400 0.4299
0.3976 1.0183 500 0.4117
0.3582 1.2220 600 0.3969
0.3537 1.4257 700 0.3871
0.3379 1.6293 800 0.3749
0.3182 1.8330 900 0.3629
0.3198 2.0367 1000 0.3572
0.2771 2.2403 1100 0.3505
0.2886 2.4440 1200 0.3482
0.2707 2.6477 1300 0.3457
0.2777 2.8513 1400 0.3406
0.2615 3.0550 1500 0.3337
0.2361 3.2587 1600 0.3320
0.2436 3.4623 1700 0.3319
0.2375 3.6660 1800 0.3284
0.2321 3.8697 1900 0.3282
0.224 4.0733 2000 0.3255
0.211 4.2770 2100 0.3270
0.203 4.4807 2200 0.3257
0.2074 4.6843 2300 0.3227
0.2185 4.8880 2400 0.3234
0.2117 5.0916 2500 0.3232
0.1913 5.2953 2600 0.3228
0.1921 5.4990 2700 0.3219
0.1888 5.7026 2800 0.3217
0.1925 5.9063 2900 0.3216
0.1955 6.1100 3000 0.3212

Framework versions

  • PEFT 0.12.1.dev0
  • Transformers 4.44.0
  • Pytorch 2.4.0
  • Datasets 2.21.0
  • Tokenizers 0.19.1
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