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whisper-small-diarization-0.2

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+ ---
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+ license: apache-2.0
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+ base_model: openai/whisper-small
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: whisper-small-diarization-0.2
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+ results: []
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # whisper-small-diarization-0.2
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+
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+ This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.4057
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+ - Speech Scored: 802.6678
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+ - Speech Miss: 209.2589
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+ - Speech Falarm: 9.0497
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+ - Speaker Miss: 412.5650
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+ - Speaker Falarm: 185.8256
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+ - Speaker Error: 153.1979
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+ - Speaker Correct: 1198.4045
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+ - Diarization Error: 751.5885
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+ - Frames: 1500.0
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+ - Speaker Wide Frames: 1564.7402
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+ - Speech Scored Ratio: 0.5351
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+ - Speech Miss Ratio: 0.1395
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+ - Speech Falarm Ratio: 0.0060
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+ - Speaker Correct Ratio: 0.7989
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+ - Speaker Miss Ratio: 0.2382
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+ - Speaker Falarm Ratio: 0.1203
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+ - Speaker Error Ratio: 0.0831
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+ - Diarization Error Ratio: 0.4416
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 1e-05
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+ - train_batch_size: 16
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+ - eval_batch_size: 24
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+ - seed: 42
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: linear
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+ - lr_scheduler_warmup_ratio: 0.05
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+ - num_epochs: 10
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+ - mixed_precision_training: Native AMP
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Speech Scored | Speech Miss | Speech Falarm | Speaker Miss | Speaker Falarm | Speaker Error | Speaker Correct | Diarization Error | Frames | Speaker Wide Frames | Speech Scored Ratio | Speech Miss Ratio | Speech Falarm Ratio | Speaker Correct Ratio | Speaker Miss Ratio | Speaker Falarm Ratio | Speaker Error Ratio | Diarization Error Ratio |
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+ |:-------------:|:-----:|:----:|:---------------:|:-------------:|:-----------:|:-------------:|:------------:|:--------------:|:-------------:|:---------------:|:-----------------:|:------:|:-------------------:|:-------------------:|:-----------------:|:-------------------:|:---------------------:|:------------------:|:--------------------:|:-------------------:|:-----------------------:|
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+ | 0.4753 | 1.0 | 225 | 0.4855 | 731.3740 | 280.5527 | 69.0541 | 614.8317 | 199.7986 | 151.0314 | 1127.7690 | 965.6617 | 1500.0 | 1564.7402 | 0.4876 | 0.1870 | 0.0460 | 0.7518 | 0.3772 | 0.1827 | 0.0796 | 0.6395 |
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+ | 0.4572 | 2.0 | 450 | 0.4857 | 642.0541 | 369.8727 | 29.7105 | 773.0375 | 89.8413 | 131.1212 | 1124.9596 | 994.0 | 1500.0 | 1564.7402 | 0.4280 | 0.2466 | 0.0198 | 0.7500 | 0.4566 | 0.0839 | 0.0709 | 0.6114 |
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+ | 0.4638 | 3.0 | 675 | 0.4618 | 748.0445 | 263.8823 | 43.8745 | 466.9677 | 356.8117 | 116.3025 | 1147.8718 | 940.0820 | 1500.0 | 1564.7402 | 0.4987 | 0.1759 | 0.0292 | 0.7652 | 0.2922 | 0.2364 | 0.0631 | 0.5917 |
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+ | 0.4423 | 4.0 | 900 | 0.4477 | 740.9529 | 270.9738 | 30.4473 | 509.6905 | 235.4464 | 132.9747 | 1162.9712 | 878.1116 | 1500.0 | 1564.7402 | 0.4940 | 0.1806 | 0.0203 | 0.7753 | 0.3072 | 0.1581 | 0.0712 | 0.5365 |
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+ | 0.4164 | 5.0 | 1125 | 0.4309 | 737.6809 | 274.2459 | 12.4037 | 512.4150 | 173.0157 | 138.8300 | 1178.9698 | 824.2607 | 1500.0 | 1564.7402 | 0.4918 | 0.1828 | 0.0083 | 0.7860 | 0.3010 | 0.1130 | 0.0754 | 0.4893 |
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+ | 0.3924 | 6.0 | 1350 | 0.4112 | 812.0453 | 199.8814 | 13.5414 | 382.1125 | 253.1543 | 140.2999 | 1194.7111 | 775.5667 | 1500.0 | 1564.7402 | 0.5414 | 0.1333 | 0.0090 | 0.7965 | 0.2235 | 0.1713 | 0.0755 | 0.4702 |
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+ | 0.3765 | 7.0 | 1575 | 0.4085 | 806.7515 | 205.1752 | 12.1369 | 405.6992 | 202.0323 | 149.4699 | 1197.7762 | 757.2014 | 1500.0 | 1564.7402 | 0.5378 | 0.1368 | 0.0081 | 0.7985 | 0.2361 | 0.1250 | 0.0829 | 0.4439 |
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+ | 0.3814 | 8.0 | 1800 | 0.4051 | 802.6016 | 209.3252 | 9.5911 | 398.2677 | 213.9582 | 144.1378 | 1199.8329 | 756.3636 | 1500.0 | 1564.7402 | 0.5351 | 0.1396 | 0.0064 | 0.7999 | 0.2367 | 0.1275 | 0.0794 | 0.4436 |
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+ | 0.3965 | 9.0 | 2025 | 0.4111 | 768.8736 | 243.0532 | 6.9250 | 474.9355 | 148.3069 | 146.9695 | 1194.2729 | 770.2119 | 1500.0 | 1564.7402 | 0.5126 | 0.1620 | 0.0046 | 0.7962 | 0.2742 | 0.0932 | 0.0806 | 0.4480 |
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+ | 0.4048 | 10.0 | 2250 | 0.4057 | 802.6678 | 209.2589 | 9.0497 | 412.5650 | 185.8256 | 153.1979 | 1198.4045 | 751.5885 | 1500.0 | 1564.7402 | 0.5351 | 0.1395 | 0.0060 | 0.7989 | 0.2382 | 0.1203 | 0.0831 | 0.4416 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.36.2
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+ - Pytorch 2.0.0
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+ - Datasets 2.16.1
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+ - Tokenizers 0.15.0