transformers tensorboard safetensors whisper automatic-speech-recognition generated_from_trainer base_model:smutuvi/whisper-small-sw-common-voice license:apache-2.0 endpoints_compatible region:us
---
license: apache-2.0
base_model: smutuvi/whisper-small-sw-common-voice
tags:
- generated_from_trainer
model-index:
- name: whisper-small-sw-common-voice-ndizi-248
  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-sw-common-voice-ndizi-248

This model is a fine-tuned version of [smutuvi/whisper-small-sw-common-voice](https://huggingface.co/smutuvi/whisper-small-sw-common-voice) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3100

## 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: 8
- 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
- num_epochs: 100
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.6298        | 1.0   | 28   | 1.2171          |
| 1.1514        | 2.0   | 56   | 1.0364          |
| 0.9175        | 3.0   | 84   | 0.9578          |
| 0.6885        | 4.0   | 112  | 0.9664          |
| 0.5841        | 5.0   | 140  | 1.0001          |
| 0.3397        | 6.0   | 168  | 1.0233          |
| 0.3166        | 7.0   | 196  | 1.0291          |
| 0.2313        | 8.0   | 224  | 1.0749          |
| 0.1457        | 9.0   | 252  | 1.0857          |
| 0.1036        | 10.0  | 280  | 1.0689          |
| 0.0644        | 11.0  | 308  | 1.1099          |
| 0.072         | 12.0  | 336  | 1.1080          |
| 0.0519        | 13.0  | 364  | 1.1119          |
| 0.0312        | 14.0  | 392  | 1.1747          |
| 0.0331        | 15.0  | 420  | 1.1441          |
| 0.02          | 16.0  | 448  | 1.1413          |
| 0.017         | 17.0  | 476  | 1.1880          |
| 0.0157        | 18.0  | 504  | 1.1564          |
| 0.0146        | 19.0  | 532  | 1.1627          |
| 0.013         | 20.0  | 560  | 1.2088          |
| 0.0071        | 21.0  | 588  | 1.2054          |
| 0.006         | 22.0  | 616  | 1.2113          |
| 0.0066        | 23.0  | 644  | 1.2269          |
| 0.0073        | 24.0  | 672  | 1.1721          |
| 0.0064        | 25.0  | 700  | 1.1878          |
| 0.0084        | 26.0  | 728  | 1.1701          |
| 0.0024        | 27.0  | 756  | 1.2221          |
| 0.0056        | 28.0  | 784  | 1.2072          |
| 0.005         | 29.0  | 812  | 1.1742          |
| 0.0032        | 30.0  | 840  | 1.1930          |
| 0.0021        | 31.0  | 868  | 1.1996          |
| 0.0008        | 32.0  | 896  | 1.2344          |
| 0.0014        | 33.0  | 924  | 1.2153          |
| 0.0018        | 34.0  | 952  | 1.2324          |
| 0.0013        | 35.0  | 980  | 1.2281          |
| 0.0011        | 36.0  | 1008 | 1.2223          |
| 0.0006        | 37.0  | 1036 | 1.2326          |
| 0.0011        | 38.0  | 1064 | 1.2250          |
| 0.0007        | 39.0  | 1092 | 1.2270          |
| 0.001         | 40.0  | 1120 | 1.2226          |
| 0.0017        | 41.0  | 1148 | 1.2255          |
| 0.0011        | 42.0  | 1176 | 1.2175          |
| 0.0011        | 43.0  | 1204 | 1.2302          |
| 0.0025        | 44.0  | 1232 | 1.2176          |
| 0.0021        | 45.0  | 1260 | 1.2450          |
| 0.0016        | 46.0  | 1288 | 1.3209          |
| 0.0023        | 47.0  | 1316 | 1.2245          |
| 0.0021        | 48.0  | 1344 | 1.2601          |
| 0.0024        | 49.0  | 1372 | 1.2703          |
| 0.002         | 50.0  | 1400 | 1.2674          |
| 0.0011        | 51.0  | 1428 | 1.2644          |
| 0.0032        | 52.0  | 1456 | 1.2901          |
| 0.0007        | 53.0  | 1484 | 1.2652          |
| 0.0033        | 54.0  | 1512 | 1.2901          |
| 0.0009        | 55.0  | 1540 | 1.2584          |
| 0.0012        | 56.0  | 1568 | 1.2542          |
| 0.0013        | 57.0  | 1596 | 1.2607          |
| 0.0006        | 58.0  | 1624 | 1.2733          |
| 0.0004        | 59.0  | 1652 | 1.2763          |
| 0.0003        | 60.0  | 1680 | 1.2780          |
| 0.0003        | 61.0  | 1708 | 1.2799          |
| 0.0003        | 62.0  | 1736 | 1.2808          |
| 0.0003        | 63.0  | 1764 | 1.2821          |
| 0.0003        | 64.0  | 1792 | 1.2844          |
| 0.0003        | 65.0  | 1820 | 1.2863          |
| 0.0003        | 66.0  | 1848 | 1.2875          |
| 0.0003        | 67.0  | 1876 | 1.2888          |
| 0.0003        | 68.0  | 1904 | 1.2910          |
| 0.0002        | 69.0  | 1932 | 1.2919          |
| 0.0002        | 70.0  | 1960 | 1.2930          |
| 0.0002        | 71.0  | 1988 | 1.2947          |
| 0.0002        | 72.0  | 2016 | 1.2955          |
| 0.0002        | 73.0  | 2044 | 1.2967          |
| 0.0002        | 74.0  | 2072 | 1.2974          |
| 0.0002        | 75.0  | 2100 | 1.2989          |
| 0.0002        | 76.0  | 2128 | 1.2997          |
| 0.0002        | 77.0  | 2156 | 1.3006          |
| 0.0002        | 78.0  | 2184 | 1.3011          |
| 0.0002        | 79.0  | 2212 | 1.3019          |
| 0.0002        | 80.0  | 2240 | 1.3029          |
| 0.0002        | 81.0  | 2268 | 1.3035          |
| 0.0002        | 82.0  | 2296 | 1.3040          |
| 0.0002        | 83.0  | 2324 | 1.3050          |
| 0.0002        | 84.0  | 2352 | 1.3056          |
| 0.0002        | 85.0  | 2380 | 1.3057          |
| 0.0002        | 86.0  | 2408 | 1.3065          |
| 0.0002        | 87.0  | 2436 | 1.3066          |
| 0.0002        | 88.0  | 2464 | 1.3078          |
| 0.0002        | 89.0  | 2492 | 1.3075          |
| 0.0002        | 90.0  | 2520 | 1.3080          |
| 0.0002        | 91.0  | 2548 | 1.3083          |
| 0.0002        | 92.0  | 2576 | 1.3091          |
| 0.0002        | 93.0  | 2604 | 1.3091          |
| 0.0002        | 94.0  | 2632 | 1.3091          |
| 0.0002        | 95.0  | 2660 | 1.3097          |
| 0.0002        | 96.0  | 2688 | 1.3098          |
| 0.0002        | 97.0  | 2716 | 1.3102          |
| 0.0002        | 98.0  | 2744 | 1.3102          |
| 0.0002        | 99.0  | 2772 | 1.3099          |
| 0.0002        | 100.0 | 2800 | 1.3100          |


### Framework versions

- Transformers 4.37.0.dev0
- Pytorch 2.1.1+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
