metadata

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

Whisper Small - Greek (el)

This model is a fine-tuned version of 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