---
language:
- lb
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- google/fleurs
metrics:
- wer
model-index:
- name: Whisper tiny LB - AKABI
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: google/fleurs
      type: google/fleurs
      config: lb_lu
      split: test
      args: lb_lu
    metrics:
    - name: Wer
      type: wer
      value: 60.18671593892832
---

<!-- 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 tiny LB - AKABI

This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the google/fleurs dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4215
- Wer Ortho: 62.8649
- Wer: 60.1867

## 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: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- training_steps: 4000

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:-------:|
| 0.9979        | 1.37  | 250  | 1.5394          | 73.1448   | 73.3298 |
| 0.6784        | 2.75  | 500  | 1.2998          | 66.9095   | 64.8060 |
| 0.3773        | 4.12  | 750  | 1.2317          | 63.9250   | 61.5385 |
| 0.2906        | 5.49  | 1000 | 1.2117          | 63.0759   | 60.3958 |
| 0.2052        | 6.87  | 1250 | 1.2157          | 64.1913   | 62.0685 |
| 0.1155        | 8.24  | 1500 | 1.2432          | 61.6791   | 59.6130 |
| 0.0912        | 9.62  | 1750 | 1.2684          | 63.0056   | 60.3229 |
| 0.0698        | 10.99 | 2000 | 1.2937          | 63.6788   | 60.9598 |
| 0.0396        | 12.36 | 2250 | 1.3224          | 62.7996   | 60.2451 |
| 0.0309        | 13.74 | 2500 | 1.3480          | 62.1514   | 59.4622 |
| 0.0205        | 15.11 | 2750 | 1.3696          | 62.1715   | 59.5303 |
| 0.017         | 16.48 | 3000 | 1.3895          | 62.0761   | 59.8074 |
| 0.0151        | 17.86 | 3250 | 1.4016          | 62.7745   | 60.0360 |
| 0.0125        | 19.23 | 3500 | 1.4126          | 62.8900   | 60.5952 |
| 0.012         | 20.6  | 3750 | 1.4202          | 63.0709   | 60.3909 |
| 0.0115        | 21.98 | 4000 | 1.4215          | 62.8649   | 60.1867 |


### Framework versions

- Transformers 4.32.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3