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---
license: apache-2.0
tags:
- generated_from_trainer
base_model: openai/whisper-small
datasets:
- mozilla-foundation/fsc-audio-dataset
metrics:
- wer
model-index:
- name: Personalized Whisper Small - Wei Fang
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: fsc-audio-dataset
type: mozilla-foundation/fsc-audio-dataset
metrics:
- type: wer
value: 8.372290692732681
name: Wer
---
<!-- 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. -->
# Personalized Whisper Small - Wei Fang
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the fsc-audio-dataset dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2946
- Wer: 8.3723
## 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: 32
- 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: 500
- training_steps: 4000
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.9814 | 0.32 | 100 | 0.8164 | 13.2172 |
| 0.3013 | 0.64 | 200 | 0.2578 | 11.7722 |
| 0.2074 | 0.96 | 300 | 0.2192 | 10.4972 |
| 0.1429 | 1.28 | 400 | 0.2245 | 11.0072 |
| 0.1565 | 1.6 | 500 | 0.2102 | 10.6247 |
| 0.1554 | 1.92 | 600 | 0.2137 | 11.2197 |
| 0.0684 | 2.24 | 700 | 0.2139 | 8.8823 |
| 0.0717 | 2.56 | 800 | 0.2142 | 9.6898 |
| 0.0795 | 2.88 | 900 | 0.2128 | 9.2223 |
| 0.0329 | 3.21 | 1000 | 0.2341 | 9.3073 |
| 0.03 | 3.53 | 1100 | 0.2324 | 8.9673 |
| 0.0319 | 3.85 | 1200 | 0.2365 | 9.0948 |
| 0.0137 | 4.17 | 1300 | 0.2403 | 9.0523 |
| 0.0145 | 4.49 | 1400 | 0.2470 | 8.3723 |
| 0.0145 | 4.81 | 1500 | 0.2596 | 9.4348 |
| 0.0067 | 5.13 | 1600 | 0.2544 | 8.9248 |
| 0.0088 | 5.45 | 1700 | 0.2553 | 8.4573 |
| 0.0065 | 5.77 | 1800 | 0.2729 | 8.8823 |
| 0.0018 | 6.09 | 1900 | 0.2680 | 8.7973 |
| 0.0023 | 6.41 | 2000 | 0.2710 | 9.0948 |
| 0.0018 | 6.73 | 2100 | 0.2762 | 8.8398 |
| 0.002 | 7.05 | 2200 | 0.2717 | 8.5848 |
| 0.0011 | 7.37 | 2300 | 0.2784 | 8.5423 |
| 0.0012 | 7.69 | 2400 | 0.2797 | 8.4573 |
| 0.0011 | 8.01 | 2500 | 0.2782 | 8.3723 |
| 0.0007 | 8.33 | 2600 | 0.2838 | 8.1598 |
| 0.0007 | 8.65 | 2700 | 0.2826 | 8.2448 |
| 0.0013 | 8.97 | 2800 | 0.2835 | 8.4148 |
| 0.0006 | 9.29 | 2900 | 0.2913 | 8.2448 |
| 0.0006 | 9.62 | 3000 | 0.2906 | 8.4148 |
| 0.001 | 9.94 | 3100 | 0.2886 | 8.6273 |
| 0.0005 | 10.26 | 3200 | 0.2890 | 8.3723 |
| 0.0005 | 10.58 | 3300 | 0.2905 | 8.3723 |
| 0.0005 | 10.9 | 3400 | 0.2917 | 8.4573 |
| 0.0008 | 11.22 | 3500 | 0.2927 | 8.3723 |
| 0.0019 | 11.54 | 3600 | 0.2932 | 8.3723 |
| 0.0004 | 11.86 | 3700 | 0.2939 | 8.3723 |
| 0.0004 | 12.18 | 3800 | 0.2941 | 8.3723 |
| 0.0005 | 12.5 | 3900 | 0.2944 | 8.3723 |
| 0.0005 | 12.82 | 4000 | 0.2946 | 8.3723 |
### Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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