Update README.md

README.md

@@ -1,6 +1,7 @@
 ---
 model_type: gpt2
 model_name_or_path: gpt2-medium
+model_filename: pytorch_model.bin
 hidden_size: 2048
 num_hidden_layers: 12
 num_attention_heads: 12
@@ -27,19 +28,31 @@ pipeline_tag: conversational
 ---
 ## Hyperameters used
 
-model_type: gpt2
-model_name_or_path: gpt2-medium  # Replace with the actual model architecture name if different
-hidden_size: 2048
-num_hidden_layers: 12
-num_attention_heads: 12
-intermediate_size: 3072  # Adjusted for model efficiency
-hidden_dropout_prob: 0.1
-attention_probs_dropout_prob: 0.1
-max_position_embeddings: 1024
-type_vocab_size: 1
-initializer_range: 0.02
-layer_norm_eps: 1e-05
-vocab_size: 50257
+Certainly! Here's a consolidated list of hyperparameters for your QNetworkGPT2 RL model:
+
+- `input_dim`: Input dimension for the RL agent.
+- `output_dim`: Output dimension for the RL agent.
+- `hidden_dim`: Hidden dimension for the RL agent.
+- `num_episodes`: Number of training episodes.
+- `generate_interval`: Interval for text generation during training.
+- `load_path`: Path to load a pre-trained model.
+- `model_name`: GPT-2 model architecture name.
+- `max_new_tokens`: Maximum new tokens allowed during text generation.
+- `max_length`: Maximum sequence length for input data.
+- `sequence_length`: Length of sequences in the dataset.
+- `batch_size`: Batch size for training.
+- `learning_rate`: Learning rate for optimization.
+- `gamma`: Discount factor for rewards.
+- `clip_epsilon`: Epsilon value for policy loss clipping.
+- `entropy_beta`: Beta value for entropy regularization.
+- `epsilon_start`: Initial epsilon for epsilon-greedy exploration.
+- `epsilon_end`: Minimum epsilon value.
+- `epsilon_decay`: Epsilon decay rate.
+- `heuristic_fn`: Heuristic function for action selection.
+- `max_new_tokens`: Maximum new tokens allowed during text generation.
+- `save_path`: Path to save the trained model.
+
+Researchers can use these hyperparameters to configure and train their QNetworkGPT2 RL models effectively for text generation tasks.
 ---
 
 # QNetworkGPT2: Reinventing Text Generation with AI 📝🤖