File size: 7,403 Bytes
4a73725 0d1ee9f 4a73725 0d1ee9f 4a73725 0d1ee9f 4a73725 0d1ee9f 4a73725 |
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 |
---
library_name: transformers
language:
- he
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- hf-asr-leaderboard
- generated_from_trainer
metrics:
- wer
model-index:
- name: he-cantillation
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# he-cantillation
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:
- Loss: 4.7623
- Wer: 98.8781
- Avg Precision Exact: 0.0291
- Avg Recall Exact: 0.0505
- Avg F1 Exact: 0.0356
- Avg Precision Letter Shift: 0.0493
- Avg Recall Letter Shift: 0.0876
- Avg F1 Letter Shift: 0.0605
- Avg Precision Word Level: 0.0685
- Avg Recall Word Level: 0.1200
- Avg F1 Word Level: 0.0833
- Avg Precision Word Shift: 0.1707
- Avg Recall Word Shift: 0.3059
- Avg F1 Word Shift: 0.2088
- Precision Median Exact: 0.0
- Recall Median Exact: 0.0
- F1 Median Exact: 0.0
- Precision Max Exact: 0.4444
- Recall Max Exact: 1.0
- F1 Max Exact: 0.4286
- Precision Min Exact: 0.0
- Recall Min Exact: 0.0
- F1 Min Exact: 0.0
- Precision Min Letter Shift: 0.0
- Recall Min Letter Shift: 0.0
- F1 Min Letter Shift: 0.0
- Precision Min Word Level: 0.0
- Recall Min Word Level: 0.0
- F1 Min Word Level: 0.0
- Precision Min Word Shift: 0.0
- Recall Min Word Shift: 0.0
- F1 Min Word Shift: 0.0
## 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: 1e-05
- train_batch_size: 16
- eval_batch_size: 2
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- training_steps: 100000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Avg Precision Exact | Avg Recall Exact | Avg F1 Exact | Avg Precision Letter Shift | Avg Recall Letter Shift | Avg F1 Letter Shift | Avg Precision Word Level | Avg Recall Word Level | Avg F1 Word Level | Avg Precision Word Shift | Avg Recall Word Shift | Avg F1 Word Shift | Precision Median Exact | Recall Median Exact | F1 Median Exact | Precision Max Exact | Recall Max Exact | F1 Max Exact | Precision Min Exact | Recall Min Exact | F1 Min Exact | Precision Min Letter Shift | Recall Min Letter Shift | F1 Min Letter Shift | Precision Min Word Level | Recall Min Word Level | F1 Min Word Level | Precision Min Word Shift | Recall Min Word Shift | F1 Min Word Shift |
|:-------------:|:-------:|:------:|:---------------:|:-------:|:-------------------:|:----------------:|:------------:|:--------------------------:|:-----------------------:|:-------------------:|:------------------------:|:---------------------:|:-----------------:|:------------------------:|:---------------------:|:-----------------:|:----------------------:|:-------------------:|:---------------:|:-------------------:|:----------------:|:------------:|:-------------------:|:----------------:|:------------:|:--------------------------:|:-----------------------:|:-------------------:|:------------------------:|:---------------------:|:-----------------:|:------------------------:|:---------------------:|:-----------------:|
| 0.0276 | 3.0030 | 20000 | 3.0853 | 98.7760 | 0.0336 | 0.0472 | 0.0380 | 0.0581 | 0.0831 | 0.0658 | 0.0801 | 0.1144 | 0.0904 | 0.2032 | 0.3029 | 0.2334 | 0.0213 | 0.0303 | 0.0267 | 0.6667 | 0.6667 | 0.6667 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 0.0026 | 6.0060 | 40000 | 3.8257 | 98.8227 | 0.0303 | 0.0497 | 0.0364 | 0.0528 | 0.0880 | 0.0637 | 0.0728 | 0.1208 | 0.0877 | 0.1812 | 0.3095 | 0.2204 | 0.0 | 0.0 | 0.0 | 0.75 | 0.75 | 0.75 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 0.0004 | 9.0090 | 60000 | 4.3074 | 99.0124 | 0.0283 | 0.0504 | 0.0347 | 0.0476 | 0.0872 | 0.0590 | 0.0641 | 0.1169 | 0.0792 | 0.1600 | 0.2986 | 0.1987 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 0.8 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 0.0001 | 12.0120 | 80000 | 4.6534 | 98.8315 | 0.0295 | 0.0516 | 0.0361 | 0.0502 | 0.0882 | 0.0611 | 0.0687 | 0.1192 | 0.0826 | 0.1715 | 0.3112 | 0.2103 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 0.0 | 15.0150 | 100000 | 4.7623 | 98.8781 | 0.0291 | 0.0505 | 0.0356 | 0.0493 | 0.0876 | 0.0605 | 0.0685 | 0.1200 | 0.0833 | 0.1707 | 0.3059 | 0.2088 | 0.0 | 0.0 | 0.0 | 0.4444 | 1.0 | 0.4286 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
### Framework versions
- Transformers 4.49.0
- Pytorch 2.6.0+cu126
- Datasets 2.12.0
- Tokenizers 0.20.1
|