---
library_name: transformers
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-small-CV_Fleurs_AMMI_ALFFA-sw-20hrs-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-CV_Fleurs_AMMI_ALFFA-sw-20hrs-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: 0.7663
- Wer: 0.2445
- Cer: 0.0922

## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- 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    |
|:-------------:|:-------:|:-----:|:---------------:|:------:|:------:|
| 3.059         | 0.9993  | 752   | 0.7311          | 0.5301 | 0.2009 |
| 1.0691        | 2.0     | 1505  | 0.5315          | 0.3752 | 0.1488 |
| 0.6341        | 2.9993  | 2257  | 0.4776          | 0.2844 | 0.0992 |
| 0.3826        | 4.0     | 3010  | 0.4720          | 0.2725 | 0.1037 |
| 0.2525        | 4.9993  | 3762  | 0.4979          | 0.2961 | 0.1204 |
| 0.1966        | 6.0     | 4515  | 0.5199          | 0.2599 | 0.0924 |
| 0.1748        | 6.9993  | 5267  | 0.5406          | 0.3148 | 0.1430 |
| 0.1642        | 8.0     | 6020  | 0.5674          | 0.2654 | 0.0958 |
| 0.1639        | 8.9993  | 6772  | 0.5802          | 0.2621 | 0.1186 |
| 0.1601        | 10.0    | 7525  | 0.6058          | 0.2652 | 0.1026 |
| 0.155         | 10.9993 | 8277  | 0.6102          | 0.2733 | 0.1036 |
| 0.1289        | 12.0    | 9030  | 0.6181          | 0.2613 | 0.0996 |
| 0.1105        | 12.9993 | 9782  | 0.6233          | 0.2615 | 0.0984 |
| 0.0981        | 14.0    | 10535 | 0.6377          | 0.2493 | 0.0931 |
| 0.089         | 14.9993 | 11287 | 0.6352          | 0.2612 | 0.1007 |
| 0.0761        | 16.0    | 12040 | 0.6494          | 0.2518 | 0.0972 |
| 0.0722        | 16.9993 | 12792 | 0.6665          | 0.2470 | 0.0917 |
| 0.063         | 18.0    | 13545 | 0.6687          | 0.2428 | 0.0898 |
| 0.0584        | 18.9993 | 14297 | 0.6715          | 0.2550 | 0.0984 |
| 0.0551        | 20.0    | 15050 | 0.6856          | 0.2506 | 0.0935 |
| 0.0503        | 20.9993 | 15802 | 0.6928          | 0.2480 | 0.0969 |
| 0.0464        | 22.0    | 16555 | 0.6887          | 0.2432 | 0.0913 |
| 0.0426        | 22.9993 | 17307 | 0.7118          | 0.2457 | 0.0925 |
| 0.0376        | 24.0    | 18060 | 0.7240          | 0.2357 | 0.0882 |
| 0.0376        | 24.9993 | 18812 | 0.7268          | 0.2458 | 0.0946 |
| 0.0339        | 26.0    | 19565 | 0.7335          | 0.2492 | 0.0931 |
| 0.0313        | 26.9993 | 20317 | 0.7185          | 0.2419 | 0.0908 |
| 0.0322        | 28.0    | 21070 | 0.7345          | 0.2396 | 0.0919 |
| 0.0313        | 28.9993 | 21822 | 0.7401          | 0.2432 | 0.0937 |
| 0.0268        | 30.0    | 22575 | 0.7576          | 0.2474 | 0.0946 |
| 0.0267        | 30.9993 | 23327 | 0.7653          | 0.2432 | 0.0938 |
| 0.025         | 32.0    | 24080 | 0.7593          | 0.2432 | 0.0940 |
| 0.0241        | 32.9993 | 24832 | 0.7670          | 0.2443 | 0.0930 |
| 0.0238        | 34.0    | 25585 | 0.7663          | 0.2445 | 0.0922 |


### Framework versions

- Transformers 4.46.1
- Pytorch 2.1.0+cu118
- Datasets 3.1.0
- Tokenizers 0.20.1