File size: 2,323 Bytes
14fffed ab9cdbf 14fffed ab9cdbf 0e6dbee 14fffed ab9cdbf 14fffed ab9cdbf 14fffed ab9cdbf 14fffed 51a9fa3 14fffed 51a9fa3 14fffed 51a9fa3 14fffed ab9cdbf 14fffed 51a9fa3 14fffed 51a9fa3 |
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 |
---
library_name: transformers
license: apache-2.0
base_model: openai/whisper-base
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-base-zh
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-base-zh
This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3426
- Wer: 78.6221
## 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: 5e-06
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Use 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: 100
- training_steps: 4000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.4992 | 0.2075 | 100 | 0.4841 | 93.0091 |
| 0.4325 | 0.4149 | 200 | 0.4223 | 82.7761 |
| 0.4028 | 0.6224 | 300 | 0.3979 | 81.6616 |
| 0.3866 | 0.8299 | 400 | 0.3846 | 79.8886 |
| 0.3322 | 1.0373 | 500 | 0.3731 | 80.3951 |
| 0.3108 | 1.2448 | 600 | 0.3672 | 79.2300 |
| 0.3139 | 1.4523 | 700 | 0.3601 | 79.1287 |
| 0.324 | 1.6598 | 800 | 0.3558 | 78.7741 |
| 0.2629 | 1.8672 | 900 | 0.3525 | 78.1155 |
| 0.2421 | 2.0747 | 1000 | 0.3521 | 78.5208 |
| 0.217 | 2.2822 | 1100 | 0.3495 | 78.3688 |
| 0.2071 | 2.4896 | 1200 | 0.3490 | 78.5714 |
| 0.2183 | 2.6971 | 1300 | 0.3452 | 78.6727 |
| 0.2158 | 2.9046 | 1400 | 0.3426 | 78.6221 |
### Framework versions
- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
|