File size: 2,730 Bytes
2cf1062 |
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 |
---
language:
- en
license: apache-2.0
base_model: openai/whisper-base
tags:
- hf-asr-leaderboard
- generated_from_trainer
metrics:
- wer
model-index:
- name: Whisper Small Five 20K - Chee Li
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. -->
# Whisper Small Five 20K - Chee Li
This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co./openai/whisper-base) on the Google Fleurs dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5771
- Wer: 22.0375
## 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: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2500
- training_steps: 20000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-------:|:-----:|:---------------:|:-------:|
| 0.4014 | 1.0560 | 1000 | 0.4369 | 25.7071 |
| 0.2677 | 2.1119 | 2000 | 0.3905 | 22.1327 |
| 0.1651 | 3.1679 | 3000 | 0.3856 | 21.2139 |
| 0.1102 | 4.2239 | 4000 | 0.3920 | 20.4471 |
| 0.0514 | 5.2798 | 5000 | 0.4072 | 21.2883 |
| 0.0255 | 6.3358 | 6000 | 0.4273 | 21.4687 |
| 0.0184 | 7.3918 | 7000 | 0.4442 | 21.6251 |
| 0.01 | 8.4477 | 8000 | 0.4635 | 21.3397 |
| 0.0051 | 9.5037 | 9000 | 0.4805 | 21.3867 |
| 0.0043 | 10.5597 | 10000 | 0.4924 | 21.5508 |
| 0.0025 | 11.6156 | 11000 | 0.5054 | 21.5847 |
| 0.0023 | 12.6716 | 12000 | 0.5166 | 22.0703 |
| 0.0016 | 13.7276 | 13000 | 0.5292 | 21.7509 |
| 0.0012 | 14.7835 | 14000 | 0.5375 | 21.7925 |
| 0.001 | 15.8395 | 15000 | 0.5480 | 21.9325 |
| 0.0008 | 16.8955 | 16000 | 0.5565 | 21.8866 |
| 0.0008 | 17.9514 | 17000 | 0.5638 | 21.9423 |
| 0.0005 | 19.0074 | 18000 | 0.5709 | 21.9916 |
| 0.0005 | 20.0634 | 19000 | 0.5755 | 22.0397 |
| 0.0004 | 21.1193 | 20000 | 0.5771 | 22.0375 |
### Framework versions
- Transformers 4.43.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
|