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metadata
library_name: transformers
license: apache-2.0
base_model: openai/whisper-small
tags:
  - generated_from_trainer
metrics:
  - wer
model-index:
  - name: whisper-small-CV_Fleurs_AMMI_ALFFA-sw-5hrs-v1
    results: []

whisper-small-CV_Fleurs_AMMI_ALFFA-sw-5hrs-v1

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

  • Loss: 0.9973
  • Wer: 0.3738
  • Cer: 0.1499

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: 5e-05
  • train_batch_size: 8
  • eval_batch_size: 4
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 16
  • optimizer: Use adamw_hf with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 100
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Cer Validation Loss Wer
4.7293 1.0 179 0.2498 1.0815 0.7089
1.5994 2.0 358 0.2279 0.7995 0.5767
0.9176 3.0 537 0.1536 0.6981 0.4359
0.4962 4.0 716 0.1715 0.6860 0.4339
0.2817 5.0 895 0.1346 0.7140 0.3806
0.2062 6.0 1074 0.1892 0.7249 0.4400
0.1654 7.0 1253 0.1203 0.7535 0.3534
0.1504 8.0 1432 0.1317 0.7843 0.3656
0.1499 9.0 1611 0.1677 0.7990 0.4059
0.1459 10.0 1790 0.1339 0.8195 0.3706
0.1409 11.0 1969 0.1334 0.8332 0.3632
0.1191 12.0 2148 0.1154 0.8286 0.3334
0.1046 13.0 2327 0.1385 0.8617 0.3722
0.0965 14.0 2506 0.1605 0.8756 0.4000
0.086 15.0 2685 0.1258 0.8674 0.3489
0.0747 16.0 2864 0.1688 0.8831 0.3948
0.0682 17.0 3043 0.1257 0.8814 0.3398
0.0635 18.0 3222 0.1366 0.9215 0.3569
0.0606 19.0 3401 0.1271 0.9136 0.3477
0.0477 20.0 3580 0.1273 0.9359 0.3456
0.0439 21.0 3759 0.1286 0.9150 0.3441
0.048 22.0 3938 0.1226 0.9309 0.3392
0.0429 23.0 4117 0.9718 0.3416 0.1249
0.0418 24.0 4296 0.9585 0.3389 0.1204
0.042 25.0 4475 0.9693 0.3636 0.1361
0.0353 26.0 4654 0.9719 0.3518 0.1309
0.0329 27.0 4833 0.9545 0.3617 0.1424
0.0288 28.0 5012 0.9910 0.3389 0.1257
0.0298 29.0 5191 0.9686 0.3380 0.1264
0.0242 30.0 5370 0.9915 0.3634 0.1488
0.0225 31.0 5549 0.9842 0.3349 0.1279
0.019 32.0 5728 0.9973 0.3738 0.1499

Framework versions

  • Transformers 4.46.1
  • Pytorch 2.1.0+cu118
  • Datasets 3.1.0
  • Tokenizers 0.20.1