---
library_name: transformers
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-small-Fleurs_AMMI_AFRIVOICE_LRSC-ln-109hrs-v1
  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-Fleurs_AMMI_AFRIVOICE_LRSC-ln-109hrs-v1

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9074
- Wer: 0.2063
- Cer: 0.0793

## 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: 4
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Use adamw_hf with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 100
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step   | Validation Loss | Wer    | Cer    |
|:-------------:|:-----:|:------:|:---------------:|:------:|:------:|
| 1.4677        | 1.0   | 2880   | 0.7253          | 0.6948 | 0.3565 |
| 0.6293        | 2.0   | 5760   | 0.5281          | 0.5550 | 0.3003 |
| 0.4895        | 3.0   | 8640   | 0.4502          | 0.4045 | 0.2119 |
| 0.3993        | 4.0   | 11520  | 0.4109          | 0.4834 | 0.2918 |
| 0.3241        | 5.0   | 14400  | 0.3989          | 0.4870 | 0.2655 |
| 0.2551        | 6.0   | 17280  | 0.4082          | 0.4294 | 0.2432 |
| 0.1918        | 7.0   | 20160  | 0.4232          | 0.3710 | 0.1913 |
| 0.1369        | 8.0   | 23040  | 0.4381          | 0.4223 | 0.2191 |
| 0.0967        | 9.0   | 25920  | 0.4774          | 0.3570 | 0.1636 |
| 0.0709        | 10.0  | 28800  | 0.4869          | 0.3268 | 0.1283 |
| 0.0544        | 11.0  | 31680  | 0.5251          | 0.2836 | 0.1034 |
| 0.04          | 12.0  | 34560  | 0.5354          | 0.2856 | 0.1043 |
| 0.0309        | 13.0  | 37440  | 0.5464          | 0.2683 | 0.0985 |
| 0.0247        | 14.0  | 40320  | 0.5621          | 0.2640 | 0.0933 |
| 0.021         | 15.0  | 43200  | 0.5743          | 0.2510 | 0.0862 |
| 0.0185        | 16.0  | 46080  | 0.5972          | 0.2540 | 0.0893 |
| 0.0161        | 17.0  | 48960  | 0.5969          | 0.2399 | 0.0820 |
| 0.0143        | 18.0  | 51840  | 0.6073          | 0.2394 | 0.0805 |
| 0.013         | 19.0  | 54720  | 0.6256          | 0.2350 | 0.0814 |
| 0.0117        | 20.0  | 57600  | 0.6198          | 0.2298 | 0.0800 |
| 0.0103        | 21.0  | 60480  | 0.6410          | 0.2330 | 0.0830 |
| 0.0097        | 22.0  | 63360  | 0.6626          | 0.2373 | 0.0821 |
| 0.009         | 23.0  | 66240  | 0.6666          | 0.2279 | 0.0770 |
| 0.0083        | 24.0  | 69120  | 0.6686          | 0.2269 | 0.0779 |
| 0.0075        | 25.0  | 72000  | 0.6851          | 0.2220 | 0.0793 |
| 0.0071        | 26.0  | 74880  | 0.6944          | 0.2261 | 0.0784 |
| 0.0065        | 27.0  | 77760  | 0.7010          | 0.2240 | 0.0793 |
| 0.0058        | 28.0  | 80640  | 0.6999          | 0.2282 | 0.0812 |
| 0.0055        | 29.0  | 83520  | 0.7135          | 0.2208 | 0.0778 |
| 0.0054        | 30.0  | 86400  | 0.7268          | 0.2240 | 0.0806 |
| 0.0047        | 31.0  | 89280  | 0.7210          | 0.2208 | 0.0774 |
| 0.0045        | 32.0  | 92160  | 0.7255          | 0.2180 | 0.0776 |
| 0.0045        | 33.0  | 95040  | 0.7512          | 0.2179 | 0.0776 |
| 0.0037        | 34.0  | 97920  | 0.7662          | 0.2177 | 0.0812 |
| 0.0038        | 35.0  | 100800 | 0.7562          | 0.2087 | 0.0757 |
| 0.0036        | 36.0  | 103680 | 0.7524          | 0.2093 | 0.0740 |
| 0.0033        | 37.0  | 106560 | 0.7719          | 0.2136 | 0.0783 |
| 0.003         | 38.0  | 109440 | 0.7792          | 0.2149 | 0.0764 |
| 0.0029        | 39.0  | 112320 | 0.7883          | 0.2135 | 0.0761 |
| 0.0029        | 40.0  | 115200 | 0.7960          | 0.2098 | 0.0750 |
| 0.0026        | 41.0  | 118080 | 0.7779          | 0.2072 | 0.0750 |
| 0.0026        | 42.0  | 120960 | 0.7881          | 0.2155 | 0.0784 |
| 0.0024        | 43.0  | 123840 | 0.7936          | 0.2076 | 0.0740 |
| 0.0022        | 44.0  | 126720 | 0.8039          | 0.2071 | 0.0735 |
| 0.0022        | 45.0  | 129600 | 0.8125          | 0.2055 | 0.0740 |
| 0.0021        | 46.0  | 132480 | 0.8248          | 0.2118 | 0.0749 |
| 0.0019        | 47.0  | 135360 | 0.8211          | 0.2119 | 0.0777 |
| 0.0017        | 48.0  | 138240 | 0.8212          | 0.2100 | 0.0783 |
| 0.0019        | 49.0  | 141120 | 0.8303          | 0.2052 | 0.0744 |
| 0.0018        | 50.0  | 144000 | 0.8337          | 0.2059 | 0.0761 |
| 0.0016        | 51.0  | 146880 | 0.8529          | 0.2100 | 0.0776 |
| 0.0013        | 52.0  | 149760 | 0.8497          | 0.2109 | 0.0788 |
| 0.0014        | 53.0  | 152640 | 0.8656          | 0.2115 | 0.0777 |
| 0.0013        | 54.0  | 155520 | 0.8556          | 0.2068 | 0.0784 |
| 0.0012        | 55.0  | 158400 | 0.8539          | 0.2058 | 0.0777 |
| 0.0012        | 56.0  | 161280 | 0.8640          | 0.2006 | 0.0730 |
| 0.0011        | 57.0  | 164160 | 0.8455          | 0.2037 | 0.0770 |
| 0.0011        | 58.0  | 167040 | 0.8684          | 0.2068 | 0.0778 |
| 0.001         | 59.0  | 169920 | 0.8569          | 0.2057 | 0.0771 |
| 0.0009        | 60.0  | 172800 | 0.8669          | 0.2023 | 0.0741 |
| 0.001         | 61.0  | 175680 | 0.8780          | 0.2069 | 0.0785 |
| 0.0008        | 62.0  | 178560 | 0.8928          | 0.2068 | 0.0763 |
| 0.0007        | 63.0  | 181440 | 0.8991          | 0.2052 | 0.0750 |
| 0.0009        | 64.0  | 184320 | 0.9090          | 0.2093 | 0.0799 |
| 0.0007        | 65.0  | 187200 | 0.8953          | 0.2011 | 0.0754 |
| 0.0006        | 66.0  | 190080 | 0.9095          | 0.2059 | 0.0772 |
| 0.0006        | 67.0  | 192960 | 0.9042          | 0.2004 | 0.0766 |
| 0.0005        | 68.0  | 195840 | 0.9074          | 0.2063 | 0.0793 |


### Framework versions

- Transformers 4.46.3
- Pytorch 2.1.0+cu118
- Datasets 3.1.0
- Tokenizers 0.20.3