update model name field in config

config.yaml

@@ -1,5 +1,5 @@
 model:
-  name: "voxmenthe/modernbert-imdb-sentiment"
+  name_or_path: "voxmenthe/modernbert-imdb-sentiment"
   tokenizer_name_or_path: "answerdotai/ModernBERT-base"
   max_length: 880 # 256
   dropout: 0.1

src/config.yaml

@@ -1,46 +0,0 @@
-model:
-  name: "voxmenthe/modernbert-imdb-sentiment"
-  loss_function:
-    name: "SentimentWeightedLoss" # Options: "SentimentWeightedLoss", "SentimentFocalLoss"
-    # Parameters for the chosen loss function.
-    # For SentimentFocalLoss, common params are:
-    # gamma_focal: 1.0 # (e.g., 2.0 for standard, -2.0 for reversed, 0 for none)
-    # label_smoothing_epsilon: 0.05 # (e.g., 0.0 to 0.1)
-    # For SentimentWeightedLoss, params is empty:
-    params:
-      gamma_focal: 1.0
-      label_smoothing_epsilon: 0.05
-  output_dir: "checkpoints"
-  max_length: 880 # 256
-  dropout: 0.1
-  # --- Pooling Strategy --- #
-  # Options: "cls", "mean", "cls_mean_concat", "weighted_layer", "cls_weighted_concat"
-  # "cls" uses just the [CLS] token for classification
-  # "mean" uses mean pooling over final hidden states for classification
-  # "cls_mean_concat" uses both [CLS] and mean pooling over final hidden states for classification
-  # "weighted_layer" uses a weighted combination of the final hidden states from the top N layers for classification
-  # "cls_weighted_concat" uses a weighted combination of the final hidden states from the top N layers and the [CLS] token for classification
-  
-  pooling_strategy: "mean" # Current default, change as needed
-
-  num_weighted_layers: 6 # Number of top BERT layers to use for 'weighted_layer' strategies (e.g., 1 to 12 for BERT-base)
-
-data:
-  # No specific data paths needed as we use HF datasets at the moment
-
-training:
-  epochs: 6
-  batch_size: 16
-  lr: 1e-5 # 1e-5 # 2.0e-5
-  weight_decay_rate: 0.02 # 0.01
-  resume_from_checkpoint: "" # "checkpoints/mean_epoch2_0.9361acc_0.9355f1.pt" # Path to checkpoint file, or empty to not resume
-
-inference:
-  # Default path, can be overridden
-  model_path: "checkpoints/mean_epoch5_0.9575acc_0.9575f1.pt" 
-  # Using the same max_length as training for consistency
-  max_length: 880 # 256
-
-
-# "answerdotai/ModernBERT-base"
-# "answerdotai/ModernBERT-large"