---
library_name: transformers
language:
- lg
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- Grain
metrics:
- wer
model-index:
- name: Whisper-small-lg-finetuned
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Grain
      type: Grain
    metrics:
    - name: Wer
      type: wer
      value: 0.003958390868084323
---

<!-- 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-lg-finetuned

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co./openai/whisper-small) on the Grain dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0014
- Wer: 0.0040
- Cer: 0.0013

## 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: 16
- 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_ratio: 0.1
- num_epochs: 80
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer    | Cer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|
| 1.9276        | 1.0   | 1296  | 0.4841          | 1.1593 | 0.4773 |
| 0.2693        | 2.0   | 2592  | 0.0967          | 1.2498 | 0.5777 |
| 0.0668        | 3.0   | 3888  | 0.0300          | 1.1842 | 0.5634 |
| 0.0234        | 4.0   | 5184  | 0.0162          | 0.8390 | 0.3714 |
| 0.0117        | 5.0   | 6480  | 0.0108          | 0.8158 | 0.3744 |
| 0.0072        | 6.0   | 7776  | 0.0094          | 0.4896 | 0.2288 |
| 0.0051        | 7.0   | 9072  | 0.0086          | 0.2434 | 0.1106 |
| 0.005         | 8.0   | 10368 | 0.0090          | 0.2317 | 0.1230 |
| 0.0041        | 9.0   | 11664 | 0.0064          | 0.1364 | 0.0608 |
| 0.0029        | 10.0  | 12960 | 0.0064          | 0.0704 | 0.0215 |
| 0.0025        | 11.0  | 14256 | 0.0053          | 0.0756 | 0.0495 |
| 0.0018        | 12.0  | 15552 | 0.0059          | 0.0699 | 0.0313 |
| 0.0022        | 13.0  | 16848 | 0.0036          | 0.0238 | 0.0095 |
| 0.0018        | 14.0  | 18144 | 0.0053          | 0.0426 | 0.0195 |
| 0.0013        | 15.0  | 19440 | 0.0051          | 0.0203 | 0.0059 |
| 0.0017        | 16.0  | 20736 | 0.0028          | 0.0255 | 0.0124 |
| 0.0009        | 17.0  | 22032 | 0.0031          | 0.0254 | 0.0116 |
| 0.001         | 18.0  | 23328 | 0.0038          | 0.0105 | 0.0031 |
| 0.0014        | 19.0  | 24624 | 0.0022          | 0.0109 | 0.0034 |
| 0.001         | 20.0  | 25920 | 0.0015          | 0.0108 | 0.0037 |
| 0.0009        | 21.0  | 27216 | 0.0036          | 0.0170 | 0.0047 |
| 0.0005        | 22.0  | 28512 | 0.0014          | 0.0091 | 0.0032 |
| 0.0007        | 23.0  | 29808 | 0.0014          | 0.0101 | 0.0031 |
| 0.001         | 24.0  | 31104 | 0.0020          | 0.0108 | 0.0035 |
| 0.0004        | 25.0  | 32400 | 0.0015          | 0.0093 | 0.0030 |
| 0.0006        | 26.0  | 33696 | 0.0022          | 0.0174 | 0.0076 |
| 0.0007        | 27.0  | 34992 | 0.0020          | 0.0122 | 0.0079 |
| 0.0006        | 28.0  | 36288 | 0.0016          | 0.0081 | 0.0029 |
| 0.0004        | 29.0  | 37584 | 0.0020          | 0.0110 | 0.0031 |
| 0.0007        | 30.0  | 38880 | 0.0015          | 0.0106 | 0.0037 |
| 0.0005        | 31.0  | 40176 | 0.0025          | 0.0116 | 0.0032 |
| 0.0005        | 32.0  | 41472 | 0.0016          | 0.0097 | 0.0027 |
| 0.0003        | 33.0  | 42768 | 0.0010          | 0.0087 | 0.0034 |
| 0.0004        | 34.0  | 44064 | 0.0015          | 0.0116 | 0.0062 |
| 0.0002        | 35.0  | 45360 | 0.0010          | 0.0047 | 0.0020 |
| 0.0001        | 36.0  | 46656 | 0.0009          | 0.0052 | 0.0020 |
| 0.0006        | 37.0  | 47952 | 0.0027          | 0.0097 | 0.0031 |
| 0.0003        | 38.0  | 49248 | 0.0017          | 0.0054 | 0.0016 |
| 0.0002        | 39.0  | 50544 | 0.0013          | 0.0066 | 0.0023 |
| 0.0003        | 40.0  | 51840 | 0.0023          | 0.0072 | 0.0023 |
| 0.0002        | 41.0  | 53136 | 0.0012          | 0.0044 | 0.0018 |
| 0.0003        | 42.0  | 54432 | 0.0035          | 0.0075 | 0.0031 |
| 0.0003        | 43.0  | 55728 | 0.0035          | 0.0073 | 0.0024 |
| 0.0001        | 44.0  | 57024 | 0.0014          | 0.0047 | 0.0016 |
| 0.0           | 45.0  | 58320 | 0.0014          | 0.0040 | 0.0013 |


### Framework versions

- Transformers 4.45.2
- Pytorch 2.1.0+cu118
- Datasets 3.0.1
- Tokenizers 0.20.1