---
language:
- el
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Small - Greek (el)
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: mozilla-foundation/common_voice_11_0 el
      type: mozilla-foundation/common_voice_11_0
      config: el
      split: test
      args: el
    metrics:
    - name: Wer
      type: wer
      value: 25.696508172362552
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Whisper Small - Greek (el)

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the mozilla-foundation/common_voice_11_0 el dataset 
for translation from Greek to English.
It achieves the following results on the evaluation set:
- Loss: 0.4642
- Wer: 25.6965

## Model description

This model was finetuned with the encoder frozen. Only the decoder weights have been changed by this training run. 

## Intended uses & limitations

The purpose of this model was to understand how the freezing of a part of the model might affect learning, in an effort to assess the feasibility of enabling adapters.  

## Training and evaluation data

The training was performed by streaming interleaved train+eval spits of the greek (el) subset of mozilla-foundation/common_voice_11_0 (el).
The test set was similarly used for validation. 

## Training procedure

The script used to perform the training is included in the files of this space: 

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- 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     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.0032        | 18.01 | 1000 | 0.4642          | 25.6965 |
| 0.0006        | 37.01 | 2000 | 0.5369          | 26.4395 |
| 0.0003        | 56.01 | 3000 | 0.5703          | 26.3187 |
| 0.0002        | 75.0  | 4000 | 0.5913          | 26.4302 |
| 0.0001        | 94.0  | 5000 | 0.5996          | 26.4952 |


### Framework versions

- Transformers 4.26.0.dev0
- Pytorch 1.13.0
- Datasets 2.7.1.dev0
- Tokenizers 0.12.1