---
language:
- et
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Medium et
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: ERR2020, Common Voice 11.0, FLEURS
      type: mozilla-foundation/common_voice_11_0
      config: et
      split: test
      args: et
    metrics:
    - name: Wer
      type: wer
      value: 29.720322799236126
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Whisper Medium et

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the ERR2020, Common Voice 11.0, FLEURS dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4288
- Wer: 29.7203

## 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-06
- train_batch_size: 32
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 5000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.4018        | 0.1   | 500  | 0.5518          | 39.3951 |
| 0.2654        | 0.2   | 1000 | 0.4611          | 34.3929 |
| 0.2121        | 0.3   | 1500 | 0.4346          | 32.0582 |
| 0.1752        | 0.4   | 2000 | 0.4247          | 31.1926 |
| 0.1337        | 0.5   | 2500 | 0.4216          | 30.3364 |
| 0.1281        | 0.6   | 3000 | 0.4219          | 30.0745 |
| 0.1127        | 0.7   | 3500 | 0.4252          | 29.7388 |
| 0.1254        | 0.8   | 4000 | 0.4276          | 29.8928 |
| 0.1035        | 0.9   | 4500 | 0.4292          | 29.7634 |
| 0.1114        | 1.0   | 5000 | 0.4288          | 29.7203 |


### Framework versions

- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2