Update README.md

README.md

@@ -53,7 +53,52 @@ 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: 
+The script used to perform the training `run_speech_recognition_seq2seq_streaming.py` is included in the files of this space with the following arguments:
+
+``` 
+                --model_name_or_path   "openai/whisper-small"
+                --model_revision       "main"
+                --do_train             True
+                --do_eval              True
+                --use_auth_token       False
+                --freeze_encoder       True
+                --model_index_name     "Whisper Small - Greek (el)"
+                --dataset_name         "mozilla-foundation/common_voice_11_0"
+                --dataset_config_name  "el"
+                --audio_column_name    "audio"
+                --text_column_name     "sentence"
+                --max_duration_in_seconds 30
+                --train_split_name    "train+validation"
+                --eval_split_name      "test"
+                --do_lower_case         False
+                --do_remove_punctuation False
+                --do_normalize_eval    True
+                --language             "greek"
+                --task                  "translate"
+                --shuffle_buffer_size   500
+                --output_dir             "./data/finetuningRuns/whisper-sm-el-frzEnc-xlate"
+                --per_device_train_batch_size 16
+                --gradient_accumulation_steps 4 
+                --learning_rate          1e-5
+                --warmup_steps           500
+                --max_steps              5000
+                --gradient_checkpointing True
+                --fp16                   True
+                --evaluation_strategy    "steps"
+                --per_device_eval_batch_size 8
+                --predict_with_generate  True
+                --generation_max_length  225
+                --save_steps             1000
+                --eval_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
+                --overwrite_output_dir    True
+
+```
 
 ### Training hyperparameters