---
license: apache-2.0
base_model: openai/whisper-base
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: chinese-english-whisper-finetune-take2
  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. -->

# chinese-english-whisper-finetune-take2

This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1626
- Wer: 82.7131
- Mer: 68.6675
- Cer: 28.2875

## 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: 0.0001
- 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: 1000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer      | Mer     | Cer     |
|:-------------:|:------:|:----:|:---------------:|:--------:|:-------:|:-------:|
| 0.1649        | 1.0811 | 200  | 1.2727          | 107.8031 | 70.1080 | 46.0846 |
| 0.1139        | 2.1622 | 400  | 1.2402          | 100.4802 | 71.9088 | 35.4459 |
| 0.0526        | 3.2432 | 600  | 1.2208          | 88.4754  | 69.0276 | 33.3300 |
| 0.0261        | 4.3243 | 800  | 1.1673          | 81.7527  | 66.9868 | 28.8709 |
| 0.0086        | 5.4054 | 1000 | 1.1626          | 82.7131  | 68.6675 | 28.2875 |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1