| | --- |
| | library_name: transformers |
| | license: apache-2.0 |
| | base_model: openai/whisper-small |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - wer |
| | model-index: |
| | - name: Amit65/whisper-small-multilingual |
| | results: [] |
| | language: |
| | - en |
| | - mr |
| | - hi |
| | pipeline_tag: automatic-speech-recognition |
| | --- |
| | |
| | <!-- 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. --> |
| |
|
| | # Amit65/whisper-small-multilingual |
| |
|
| | 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: 0.6283 |
| | - Wer: 80.0691 |
| |
|
| | ## Model description |
| |
|
| | More information needed |
| |
|
| | ## Intended uses & limitations |
| |
|
| | More information needed |
| |
|
| | ## Training and evaluation data |
| |
|
| | full fine tuning on custom data and evaluate on word error rate(WER) |
| |
|
| | ## Training procedure |
| | Apply full fine tuning using hugging face trainer API |
| |
|
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | Wer | |
| | |:-------------:|:------:|:----:|:---------------:|:--------:| |
| | | 3.4481 | 0.0480 | 25 | 1.7935 | 138.3641 | |
| | | 1.494 | 0.0960 | 50 | 1.3053 | 105.6452 | |
| | | 1.4092 | 0.1440 | 75 | 1.1546 | 102.6498 | |
| | | 1.1367 | 0.1919 | 100 | 1.0424 | 105.4147 | |
| | | 0.9748 | 0.2399 | 125 | 1.0038 | 116.7051 | |
| | | 0.9522 | 0.2879 | 150 | 1.0032 | 140.6682 | |
| | | 0.9114 | 0.3359 | 175 | 0.9329 | 126.2673 | |
| | | 0.9498 | 0.3839 | 200 | 0.9077 | 117.0507 | |
| | | 0.8762 | 0.4319 | 225 | 0.9359 | 97.4654 | |
| | | 0.9051 | 0.4798 | 250 | 0.8390 | 88.5945 | |
| | | 0.7941 | 0.5278 | 275 | 0.8869 | 105.2995 | |
| | | 0.8417 | 0.5758 | 300 | 0.8299 | 109.7926 | |
| | | 0.9244 | 0.6238 | 325 | 0.8105 | 79.9539 | |
| | | 0.855 | 0.6718 | 350 | 0.7960 | 87.5576 | |
| | | 0.7516 | 0.7198 | 375 | 0.7844 | 88.9401 | |
| | | 0.9119 | 0.7678 | 400 | 0.8116 | 87.4424 | |
| | | 0.7478 | 0.8157 | 425 | 0.7593 | 79.0323 | |
| | | 0.7125 | 0.8637 | 450 | 0.7280 | 84.2166 | |
| | | 0.8235 | 0.9117 | 475 | 0.7171 | 88.9401 | |
| | | 0.6975 | 0.9597 | 500 | 0.7029 | 74.8848 | |
| | | 0.5599 | 1.0077 | 525 | 0.7060 | 76.6129 | |
| | | 0.4681 | 1.0557 | 550 | 0.6891 | 100.8065 | |
| | | 0.3496 | 1.1036 | 575 | 0.6995 | 104.9539 | |
| | | 0.4196 | 1.1516 | 600 | 0.7102 | 82.4885 | |
| | | 0.3884 | 1.1996 | 625 | 0.6856 | 104.7235 | |
| | | 0.4788 | 1.2476 | 650 | 0.6745 | 81.6820 | |
| | | 0.4237 | 1.2956 | 675 | 0.6722 | 81.9124 | |
| | | 0.4001 | 1.3436 | 700 | 0.6740 | 83.2949 | |
| | | 0.3909 | 1.3916 | 725 | 0.6823 | 71.8894 | |
| | | 0.3435 | 1.4395 | 750 | 0.6934 | 75.1152 | |
| | | 0.344 | 1.4875 | 775 | 0.6810 | 72.0046 | |
| | | 0.3071 | 1.5355 | 800 | 0.6704 | 71.1982 | |
| | | 0.3392 | 1.5835 | 825 | 0.6589 | 88.3641 | |
| | | 0.3742 | 1.6315 | 850 | 0.6532 | 77.9954 | |
| | | 0.4153 | 1.6795 | 875 | 0.6363 | 79.8387 | |
| | | 0.3416 | 1.7274 | 900 | 0.6560 | 79.4931 | |
| | | 0.3121 | 1.7754 | 925 | 0.6320 | 82.0276 | |
| | | 0.2986 | 1.8234 | 950 | 0.6447 | 76.9585 | |
| | | 0.3761 | 1.8714 | 975 | 0.6420 | 75.8065 | |
| | | 0.4394 | 1.9194 | 1000 | 0.6234 | 77.5346 | |
| | | 0.3094 | 1.9674 | 1025 | 0.6430 | 81.5668 | |
| | | 0.3468 | 2.0154 | 1050 | 0.6266 | 78.5714 | |
| | | 0.25 | 2.0633 | 1075 | 0.6251 | 79.0323 | |
| | | 0.1969 | 2.1113 | 1100 | 0.6337 | 81.2212 | |
| | | 0.157 | 2.1593 | 1125 | 0.6367 | 76.8433 | |
| | | 0.2118 | 2.2073 | 1150 | 0.6414 | 74.4240 | |
| | | 0.2207 | 2.2553 | 1175 | 0.6345 | 77.4194 | |
| | | 0.1965 | 2.3033 | 1200 | 0.6414 | 76.9585 | |
| | | 0.1959 | 2.3512 | 1225 | 0.6322 | 79.6083 | |
| | | 0.1668 | 2.3992 | 1250 | 0.6394 | 81.5668 | |
| | | 0.2128 | 2.4472 | 1275 | 0.6361 | 80.4147 | |
| | | 0.173 | 2.4952 | 1300 | 0.6322 | 74.8848 | |
| | | 0.152 | 2.5432 | 1325 | 0.6312 | 73.3871 | |
| | | 0.1897 | 2.5912 | 1350 | 0.6334 | 79.0323 | |
| | | 0.1666 | 2.6392 | 1375 | 0.6339 | 81.1060 | |
| | | 0.202 | 2.6871 | 1400 | 0.6283 | 77.9954 | |
| | | 0.1511 | 2.7351 | 1425 | 0.6296 | 80.8756 | |
| | | 0.1616 | 2.7831 | 1450 | 0.6313 | 80.4147 | |
| | | 0.1482 | 2.8311 | 1475 | 0.6289 | 80.5300 | |
| | | 0.1672 | 2.8791 | 1500 | 0.6283 | 80.0691 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.52.4 |
| | - Pytorch 2.6.0+cu124 |
| | - Datasets 3.6.0 |
| | - Tokenizers 0.21.1 |
