Update README.md

README.md

@@ -16,7 +16,7 @@ datasets:
 
 This model is a fine-tuned version of [malteklaes/based-CodeBERTa-language-id-llm-module](https://huggingface.co/malteklaes/based-CodeBERTa-language-id-llm-module) on the None dataset.
 
-## Model description
+## Model description and Framework version
 
 - based on model [https://huggingface.co/malteklaes/based-CodeBERTa-language-id-llm-module_uniVienna-2](malteklaes/based-CodeBERTa-language-id-llm-module) (7 programming languages), which in turn is based on [huggingface/CodeBERTa-language-id](https://huggingface.co/huggingface/CodeBERTa-language-id) (6 programming languages)
 - model details:
@@ -130,19 +130,11 @@ myPipeline(CODE_TO_IDENTIFY_py) # output: [{'label': 'python', 'score': 0.999996
 
 ## Training and evaluation data
 
-- training arguments:
-```
-training_args = TrainingArguments(
-    output_dir="./based-CodeBERTa-language-id-llm-module_uniVienna",
-    overwrite_output_dir=True,
-    num_train_epochs=0.1,
-    per_device_train_batch_size=8,
-    save_steps=500,
-    save_total_limit=2,
-)
-```
+### Training-Datasets used
+- for Go, Java, Javascript, PHP, Python, Ruby: [code_search_net](https://huggingface.co/datasets/code_search_net)
+- for C++: [malteklaes/cpp-code-code_search_net-style](https://huggingface.co/datasets/malteklaes/cpp-code-code_search_net-style)
 
-## Training procedure
+### Training procedure
 - machine: GPU T4 (Google Colab)
   - system-RAM: 4.7/12.7 GB (during training)
   - GPU-RAM: 2.8/15.0GB
@@ -156,14 +148,17 @@ training_args = TrainingArguments(
 
 ### Training hyperparameters
 
-The following hyperparameters were used during training:
-- learning_rate: 5e-05
-- train_batch_size: 8
-- eval_batch_size: 8
-- seed: 42
-- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
-- lr_scheduler_type: linear
-- num_epochs: 0.1
+The following hyperparameters were used during training (training args):
+```
+training_args = TrainingArguments(
+    output_dir="./based-CodeBERTa-language-id-llm-module_uniVienna",
+    overwrite_output_dir=True,
+    num_train_epochs=0.1,
+    per_device_train_batch_size=8,
+    save_steps=500,
+    save_total_limit=2,
+)
+```
 
 ### Training results
 
@@ -171,11 +166,3 @@ The following hyperparameters were used during training:
 ```
 TrainOutput(global_step=24136, training_loss=0.005988701689750161, metrics={'train_runtime': 1936.0586, 'train_samples_per_second': 99.731, 'train_steps_per_second': 12.467, 'total_flos': 3197518224531456.0, 'train_loss': 0.005988701689750161, 'epoch': 0.1})
 ```
-
-
-### Framework versions
-
-- Transformers 4.39.3
-- Pytorch 2.2.1+cu121
-- Datasets 2.18.0
-- Tokenizers 0.15.2