diff --git a/config_cluster.json b/config_cluster.json
index fe227a01..d8b066d7 100644
--- a/config_cluster.json
+++ b/config_cluster.json
@@ -1,6 +1,6 @@
 {
     "run_name": "mozilla-nomask-fattn-bn",
-    "run_description": "Finetune 4700 orignal -> bn prenet - Mozilla with prenet bn, no mask, forward attn, batch group size 0",
+    "run_description": "Finetune 4702 orignal -> bn prenet - Mozilla with prenet bn, no mask, batch group size 0",
 
     "audio":{
         // Audio processing parameters
@@ -41,7 +41,7 @@
     "memory_size": 5,       //  ONLY TACOTRON - memory queue size used to queue network predictions to feed autoregressive connection. Useful if r < 5. 
     "attention_norm": "softmax",   // softmax or sigmoid. Suggested to use softmax for Tacotron2 and sigmoid for Tacotron.
     "prenet_type": "bn",    // ONLY TACOTRON2 - "original" or "bn".
-    "use_forward_attn": true,    // ONLY TACOTRON2 - if it uses forward attention. In general, it aligns faster.
+    "use_forward_attn": false,    // ONLY TACOTRON2 - if it uses forward attention. In general, it aligns faster.
     "transition_agent": false,    // ONLY TACOTRON2 - enable/disable transition agent of forward attention.
     "loss_masking": false,       // enable / disable loss masking against the sequence padding.
     "enable_eos_bos_chars": false, // enable/disable beginning of sentence and end of sentence chars.
@@ -56,11 +56,11 @@
     "tb_model_param_stats": true,     // true, plots param stats per layer on tensorboard. Might be memory consuming, but good for debugging. 
     "batch_group_size": 0,  //Number of batches to shuffle after bucketing.
 
-    "run_eval": false,
-    "test_delay_epochs": 5,  //Until attention is aligned, testing only wastes computation time.
+    "run_eval": true,
+    "test_delay_epochs": 1,  //Until attention is aligned, testing only wastes computation time.
     "data_path": "/media/erogol/data_ssd/Data/LJSpeech-1.1",  // DATASET-RELATED: can overwritten from command argument
-    "meta_file_train": "prompts_train.data",      // DATASET-RELATED: metafile for training dataloader.
-    "meta_file_val": "prompts_val.data",    // DATASET-RELATED: metafile for evaluation dataloader.
+    "meta_file_train": "metadata.txt",      // DATASET-RELATED: metafile for training dataloader.
+    "meta_file_val": "metadata_val.txt",    // DATASET-RELATED: metafile for evaluation dataloader.
     "dataset": "mozilla",      // DATASET-RELATED: one of TTS.dataset.preprocessors depending on your target dataset. Use "tts_cache" for pre-computed dataset by extract_features.py
     "min_seq_len": 0,       // DATASET-RELATED: minimum text length to use in training
     "max_seq_len": 150,     // DATASET-RELATED: maximum text length