readme: ---
  language:
  - el
  license: apache-2.0
  tags:
  - whisper-event
  - generated_from_trainer
  - whisper-large
  - mozilla-foundation/common_voice_11_0
  - greek
  datasets:
  - mozilla-foundation/common_voice_11_0
  - google/fleurs
  metrics:
  - wer
  model-index:
  - name: whisper-lg-el-intlv-xs-2
    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
      metrics:
      - name: Wer
        type: wer
        value: 9.50037147102526
  ---
  
  # whisper-lg-el-intlv-xs-2
  
  This model is a fine-tuned version of [farsipal/whisper-lg-el-intlv-xs](https://huggingface.co/farsipal/whisper-lg-el-intlv-xs) on the mozilla-foundation/common_voice_11_0,google/fleurs el,el_gr dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.2872
  - Wer: 9.5004
  
  ## Model description
  
  The model was trained on two interleaved datasets for transcription in the Greek language.
  
  ## Intended uses & limitations
  
  Transcription in the Greek language
  
  ## Training and evaluation data
  
  Training was performed on two interleaved datasets. Testing was performed on common voice 11.0 (el) test only.
  
  ## Training procedure
  ```
                  --model_name_or_path   'farsipal/whisper-lg-el-intlv-xs' \
                  --model_revision   main \
                  --do_train   True \
                  --do_eval   True \
                  --use_auth_token   False \
                  --freeze_feature_encoder   False \
                  --freeze_encoder   False \
                  --model_index_name   'whisper-lg-el-intlv-xs-2' \
                  --dataset_name 'mozilla-foundation/common_voice_11_0,google/fleurs' \
                  --dataset_config_name 'el,el_gr' \
                  --train_split_name  'train+validation,train+validation' \
                  --eval_split_name   'test,-' \
                  --text_column_name  'sentence,transcription' \
                  --audio_column_name 'audio,audio' \
                  --streaming   False \
                  --max_duration_in_seconds   30 \
                  --do_lower_case   False \
                  --do_remove_punctuation   False \
                  --do_normalize_eval   True \
                  --language   greek \
                  --task transcribe \
                  --shuffle_buffer_size   500 \
                  --output_dir   './data/finetuningRuns/whisper-lg-el-intlv-xs-2' \
                  --overwrite_output_dir   True \
                  --per_device_train_batch_size   8 \
                  --gradient_accumulation_steps  4 \
                  --learning_rate   3.5e-6 \
                  --dropout         0.15 \
                  --attention_dropout 0.05 \
                  --warmup_steps   500 \
                  --max_steps   5000 \
                  --eval_steps   1000 \
                  --gradient_checkpointing   True \
                  --cache_dir   '~/.cache' \
                  --fp16   True \
                  --evaluation_strategy   steps \
                  --per_device_eval_batch_size   8 \
                  --predict_with_generate   True \
                  --generation_max_length   225 \
                  --save_steps   1000 \
                  --logging_steps   25 \
                  --report_to   tensorboard \
                  --load_best_model_at_end   True \
                  --metric_for_best_model   wer \
                  --greater_is_better   False \
                  --push_to_hub   False  \
                  --dataloader_num_workers 6
  ```
  
  ### Training hyperparameters
  
  The following hyperparameters were used during training:
  - learning_rate: 3.5e-06
  - train_batch_size: 8
  - eval_batch_size: 8
  - seed: 42
  - gradient_accumulation_steps: 4
  - total_train_batch_size: 32
  - 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     |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|
  | 0.0813        | 2.49  | 1000 | 0.2147          | 10.8284 |
  | 0.0379        | 4.98  | 2000 | 0.2439          | 10.0111 |
  | 0.0195        | 7.46  | 3000 | 0.2767          | 9.8811  |
  | 0.0126        | 9.95  | 4000 | 0.2872          | 9.5004  |
  | 0.0103        | 12.44 | 5000 | 0.3021          | 9.6954  |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0+cu117
  - Datasets 2.8.1.dev0
  - Tokenizers 0.13.2
  