---
language:
- zh
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- Voice_Data_Collection
model-index:
- name: Whisper-Keep-train
  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-Keep-train

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Voice_Data_Collection dataset.
It achieves the following results on the evaluation set:
- Loss: 4.0346
- Cer: 736.0397

## 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: 200
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Cer      |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 3.4342        | 0.8065 | 50   | 4.1335          | 275.1466 |
| 3.0912        | 1.6129 | 100  | 4.1066          | 265.1782 |
| 2.7991        | 2.4194 | 150  | 4.0602          | 318.1326 |
| 2.6758        | 3.2258 | 200  | 4.0346          | 736.0397 |


### Framework versions

- Transformers 4.42.0.dev0
- Pytorch 2.1.2
- Datasets 2.20.0
- Tokenizers 0.19.1