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---
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_keras_callback
model-index:
- name: whisper_charsplit_new_0090
results: []
---
<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->
# whisper_charsplit_new_0090
This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.0007
- Train Accuracy: 0.0795
- Train Wermet: 10.2569
- Validation Loss: 0.5488
- Validation Accuracy: 0.0766
- Validation Wermet: 8.9133
- Epoch: 89
## 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:
- optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 1e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01}
- training_precision: float32
### Training results
| Train Loss | Train Accuracy | Train Wermet | Validation Loss | Validation Accuracy | Validation Wermet | Epoch |
|:----------:|:--------------:|:------------:|:---------------:|:-------------------:|:-----------------:|:-----:|
| 0.8733 | 0.0602 | 13.0686 | 0.6470 | 0.0676 | 11.4066 | 0 |
| 0.5740 | 0.0666 | 12.7778 | 0.5113 | 0.0706 | 11.1022 | 1 |
| 0.4553 | 0.0692 | 12.2404 | 0.4371 | 0.0723 | 10.9105 | 2 |
| 0.3813 | 0.0708 | 11.9157 | 0.3935 | 0.0733 | 9.4615 | 3 |
| 0.3292 | 0.0720 | 11.5732 | 0.3630 | 0.0740 | 9.9885 | 4 |
| 0.2886 | 0.0729 | 11.5171 | 0.3403 | 0.0745 | 9.8042 | 5 |
| 0.2561 | 0.0736 | 11.3173 | 0.3256 | 0.0749 | 9.9431 | 6 |
| 0.2282 | 0.0743 | 11.7308 | 0.3159 | 0.0752 | 9.2086 | 7 |
| 0.2036 | 0.0748 | 11.4503 | 0.3071 | 0.0754 | 9.5236 | 8 |
| 0.1820 | 0.0754 | 11.7175 | 0.3005 | 0.0756 | 10.0755 | 9 |
| 0.1628 | 0.0758 | 11.7056 | 0.2993 | 0.0757 | 9.9497 | 10 |
| 0.1450 | 0.0762 | 11.7637 | 0.2971 | 0.0758 | 10.1481 | 11 |
| 0.1287 | 0.0766 | 11.8509 | 0.3029 | 0.0759 | 10.2042 | 12 |
| 0.1140 | 0.0770 | 12.1100 | 0.3004 | 0.0760 | 10.3873 | 13 |
| 0.0998 | 0.0773 | 11.9502 | 0.3025 | 0.0761 | 10.7066 | 14 |
| 0.0872 | 0.0777 | 12.3196 | 0.3129 | 0.0759 | 10.7707 | 15 |
| 0.0760 | 0.0779 | 12.2637 | 0.3142 | 0.0761 | 10.2638 | 16 |
| 0.0651 | 0.0782 | 12.1215 | 0.3192 | 0.0761 | 10.0750 | 17 |
| 0.0547 | 0.0785 | 12.0551 | 0.3294 | 0.0761 | 10.4732 | 18 |
| 0.0463 | 0.0787 | 11.9677 | 0.3402 | 0.0760 | 10.2814 | 19 |
| 0.0386 | 0.0789 | 11.6855 | 0.3517 | 0.0760 | 10.0599 | 20 |
| 0.0318 | 0.0790 | 11.6314 | 0.3628 | 0.0760 | 9.6652 | 21 |
| 0.0262 | 0.0792 | 11.4603 | 0.3728 | 0.0760 | 10.0035 | 22 |
| 0.0224 | 0.0792 | 11.4330 | 0.3824 | 0.0760 | 9.1995 | 23 |
| 0.0181 | 0.0793 | 11.3124 | 0.3982 | 0.0759 | 9.8710 | 24 |
| 0.0142 | 0.0794 | 11.3562 | 0.4057 | 0.0760 | 9.6831 | 25 |
| 0.0118 | 0.0794 | 11.0532 | 0.4207 | 0.0759 | 9.7227 | 26 |
| 0.0101 | 0.0794 | 11.2963 | 0.4282 | 0.0760 | 9.5792 | 27 |
| 0.0114 | 0.0794 | 11.3093 | 0.4431 | 0.0758 | 9.5545 | 28 |
| 0.0109 | 0.0794 | 11.4214 | 0.4419 | 0.0760 | 9.4377 | 29 |
| 0.0084 | 0.0794 | 10.9143 | 0.4474 | 0.0760 | 9.3668 | 30 |
| 0.0043 | 0.0795 | 10.9497 | 0.4525 | 0.0761 | 9.3202 | 31 |
| 0.0036 | 0.0795 | 10.7759 | 0.4667 | 0.0761 | 9.0385 | 32 |
| 0.0047 | 0.0795 | 10.7613 | 0.4788 | 0.0759 | 9.4065 | 33 |
| 0.0130 | 0.0793 | 11.1022 | 0.4748 | 0.0760 | 9.4521 | 34 |
| 0.0074 | 0.0794 | 10.9738 | 0.4730 | 0.0760 | 9.3348 | 35 |
| 0.0032 | 0.0795 | 10.6370 | 0.4750 | 0.0762 | 8.8298 | 36 |
| 0.0020 | 0.0795 | 10.7428 | 0.4835 | 0.0762 | 9.0566 | 37 |
| 0.0014 | 0.0795 | 10.6908 | 0.4937 | 0.0761 | 9.2445 | 38 |
| 0.0035 | 0.0795 | 10.6833 | 0.5276 | 0.0757 | 8.9798 | 39 |
| 0.0120 | 0.0793 | 10.4810 | 0.4963 | 0.0760 | 8.9194 | 40 |
| 0.0045 | 0.0795 | 10.2251 | 0.5014 | 0.0761 | 8.5737 | 41 |
| 0.0028 | 0.0795 | 10.3174 | 0.4968 | 0.0762 | 8.8525 | 42 |
| 0.0023 | 0.0795 | 10.4871 | 0.5027 | 0.0762 | 8.6712 | 43 |
| 0.0024 | 0.0795 | 10.3731 | 0.5055 | 0.0762 | 8.6347 | 44 |
| 0.0041 | 0.0795 | 10.2751 | 0.5242 | 0.0760 | 8.3671 | 45 |
| 0.0070 | 0.0794 | 10.2166 | 0.5169 | 0.0760 | 8.8409 | 46 |
| 0.0037 | 0.0795 | 10.0455 | 0.5174 | 0.0762 | 8.2514 | 47 |
| 0.0023 | 0.0795 | 9.9201 | 0.5167 | 0.0763 | 8.9537 | 48 |
| 0.0008 | 0.0795 | 10.0022 | 0.5166 | 0.0764 | 8.4855 | 49 |
| 0.0006 | 0.0795 | 9.9494 | 0.5233 | 0.0763 | 8.5719 | 50 |
| 0.0069 | 0.0794 | 10.2037 | 0.5434 | 0.0759 | 8.5399 | 51 |
| 0.0083 | 0.0794 | 9.9557 | 0.5173 | 0.0762 | 8.2406 | 52 |
| 0.0032 | 0.0795 | 10.0283 | 0.5240 | 0.0763 | 9.0101 | 53 |
| 0.0018 | 0.0795 | 10.0694 | 0.5247 | 0.0763 | 8.5717 | 54 |
| 0.0008 | 0.0795 | 10.1079 | 0.5217 | 0.0764 | 8.5608 | 55 |
| 0.0005 | 0.0795 | 10.0546 | 0.5286 | 0.0764 | 8.8830 | 56 |
| 0.0007 | 0.0795 | 10.2557 | 0.5328 | 0.0764 | 8.5665 | 57 |
| 0.0006 | 0.0795 | 10.2165 | 0.5412 | 0.0763 | 8.4623 | 58 |
| 0.0124 | 0.0792 | 10.2304 | 0.5284 | 0.0762 | 9.1194 | 59 |
| 0.0044 | 0.0795 | 10.3884 | 0.5223 | 0.0764 | 8.8152 | 60 |
| 0.0015 | 0.0795 | 9.8557 | 0.5227 | 0.0764 | 8.3774 | 61 |
| 0.0005 | 0.0795 | 9.8123 | 0.5233 | 0.0765 | 8.5043 | 62 |
| 0.0003 | 0.0795 | 9.7631 | 0.5282 | 0.0765 | 8.3860 | 63 |
| 0.0003 | 0.0795 | 9.7593 | 0.5320 | 0.0765 | 8.4815 | 64 |
| 0.0002 | 0.0795 | 9.7663 | 0.5357 | 0.0765 | 8.4281 | 65 |
| 0.0034 | 0.0795 | 9.8382 | 0.5771 | 0.0758 | 8.8051 | 66 |
| 0.0123 | 0.0792 | 10.2575 | 0.5261 | 0.0763 | 9.3701 | 67 |
| 0.0027 | 0.0795 | 10.3802 | 0.5272 | 0.0764 | 8.8216 | 68 |
| 0.0011 | 0.0795 | 10.1683 | 0.5291 | 0.0764 | 8.5736 | 69 |
| 0.0012 | 0.0795 | 10.1305 | 0.5336 | 0.0765 | 8.6648 | 70 |
| 0.0008 | 0.0795 | 10.2545 | 0.5315 | 0.0765 | 9.0617 | 71 |
| 0.0006 | 0.0795 | 10.4562 | 0.5369 | 0.0765 | 9.6485 | 72 |
| 0.0032 | 0.0795 | 10.2347 | 0.5569 | 0.0763 | 8.4947 | 73 |
| 0.0062 | 0.0794 | 10.1654 | 0.5471 | 0.0763 | 8.8666 | 74 |
| 0.0029 | 0.0795 | 10.1320 | 0.5376 | 0.0765 | 8.7713 | 75 |
| 0.0012 | 0.0795 | 10.2943 | 0.5406 | 0.0765 | 8.6959 | 76 |
| 0.0006 | 0.0795 | 10.1888 | 0.5371 | 0.0767 | 8.9689 | 77 |
| 0.0005 | 0.0795 | 10.2138 | 0.5398 | 0.0766 | 8.7470 | 78 |
| 0.0016 | 0.0795 | 10.2173 | 0.5497 | 0.0764 | 8.9675 | 79 |
| 0.0065 | 0.0794 | 10.2806 | 0.5559 | 0.0763 | 9.4487 | 80 |
| 0.0028 | 0.0795 | 10.7728 | 0.5394 | 0.0766 | 8.9716 | 81 |
| 0.0012 | 0.0795 | 10.3247 | 0.5453 | 0.0765 | 8.9986 | 82 |
| 0.0013 | 0.0795 | 10.3174 | 0.5535 | 0.0765 | 8.9229 | 83 |
| 0.0011 | 0.0795 | 10.2846 | 0.5452 | 0.0766 | 9.1239 | 84 |
| 0.0007 | 0.0795 | 10.1996 | 0.5491 | 0.0766 | 8.9308 | 85 |
| 0.0034 | 0.0795 | 10.5048 | 0.5578 | 0.0764 | 8.9920 | 86 |
| 0.0038 | 0.0795 | 10.1430 | 0.5538 | 0.0765 | 9.1635 | 87 |
| 0.0019 | 0.0795 | 10.3176 | 0.5492 | 0.0766 | 8.5812 | 88 |
| 0.0007 | 0.0795 | 10.2569 | 0.5488 | 0.0766 | 8.9133 | 89 |
### Framework versions
- Transformers 4.32.0.dev0
- TensorFlow 2.12.0
- Tokenizers 0.13.3
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