File size: 2,081 Bytes
1d0d48e cd312d7 1d0d48e |
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 |
---
language:
- zh
license: apache-2.0
base_model: openai/whisper-medium
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- whucedar/datasets_stt_1
metrics:
- wer
model-index:
- name: zh-CN-model-medium-1 - whucedar
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: datasets_stt_1
type: whucedar/datasets_stt_1
args: 'config: zh, split: test'
metrics:
- name: Wer
type: wer
value: 188.47926267281105
---
<!-- 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. -->
# zh-CN-model-medium-1 - whucedar
This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the datasets_stt_1 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1323
- Wer: 188.4793
## 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: 50
- training_steps: 500
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.0241 | 1.5873 | 100 | 0.1363 | 158.9862 |
| 0.0042 | 3.1746 | 200 | 0.1312 | 239.6313 |
| 0.0043 | 4.7619 | 300 | 0.1316 | 215.2074 |
| 0.0013 | 6.3492 | 400 | 0.1312 | 203.6866 |
| 0.0006 | 7.9365 | 500 | 0.1323 | 188.4793 |
### Framework versions
- Transformers 4.42.3
- Pytorch 2.3.1+cu118
- Datasets 2.20.0
- Tokenizers 0.19.1
|