File size: 10,976 Bytes
6fa26e9 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 |
---
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_keras_callback
model-index:
- name: whisper_charsplit_new_0082
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_0082
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: 0.0028
- Train Accuracy: 0.0795
- Train Wermet: 10.7728
- Validation Loss: 0.5394
- Validation Accuracy: 0.0766
- Validation Wermet: 8.9716
- Epoch: 81
## 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 |
### Framework versions
- Transformers 4.32.0.dev0
- TensorFlow 2.12.0
- Tokenizers 0.13.3
|