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---
language:
- zh
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- thisiskeithkwan/canto
model-index:
- name: whisper-small-canto
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-canto
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co./openai/whisper-small) on the thisiskeithkwan/canto dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5061
- Cer: 0.4485
## 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: 0.0003
- train_batch_size: 2
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 5000
### Training results
| Training Loss | Epoch | Step | Validation Loss | Cer |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 1.5909 | 0.76 | 500 | 1.6890 | 0.7769 |
| 1.2636 | 1.52 | 1000 | 1.4067 | 0.7641 |
| 0.7889 | 2.27 | 1500 | 1.3118 | 0.5474 |
| 0.6929 | 3.03 | 2000 | 1.2825 | 0.5516 |
| 0.4827 | 3.79 | 2500 | 1.2360 | 0.5446 |
| 0.236 | 4.55 | 3000 | 1.3457 | 0.5044 |
| 0.0982 | 5.31 | 3500 | 1.4736 | 0.4841 |
| 0.064 | 6.07 | 4000 | 1.5103 | 0.4809 |
| 0.035 | 6.82 | 4500 | 1.5110 | 0.4563 |
| 0.0103 | 7.58 | 5000 | 1.5061 | 0.4485 |
### Framework versions
- Transformers 4.32.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.14.3
- Tokenizers 0.13.3
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