Model save

README.md

@@ -22,8 +22,7 @@ This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.1](https
 
 ## Model description
 
-https://ai.plainenglish.io/fine-tuning-the-mistral-7b-instruct-v0-1-model-with-aviationqa-dataset-06773d447c03
-
+More information needed
 
 ## Intended uses & limitations
 
@@ -31,23 +30,7 @@ More information needed
 
 ## Training and evaluation data
 
-
-The following hyperparameters were used during training:
-- learning_rate: 0.0002
-- train_batch_size: 3
-- eval_batch_size: 8
-- seed: 42
-- gradient_accumulation_steps: 2
-- total_train_batch_size: 6
-- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
-- lr_scheduler_type: constant
-- lr_scheduler_warmup_ratio: 0.03
-- num_epochs: 1
-
-The accuracy of the match Accuracy (Eval dataset and predict) for a sample of 10,000 questions is 23.21%; the AviationQA dataset has 1 Million questions related to the aviation domain. 
-
-The source code for the evaluation is here https://github.com/frank-morales2020/MLxDL/blob/main/FineTunning_Testing_For_AviationQADataset_.ipynb
-
+More information needed
 
 ## Training procedure
 
@@ -55,15 +38,15 @@ The source code for the evaluation is here https://github.com/frank-morales2020/
 
 The following hyperparameters were used during training:
 - learning_rate: 0.0002
-- train_batch_size: 3
-- eval_batch_size: 8
+- train_batch_size: 2
+- eval_batch_size: 4
 - seed: 42
 - gradient_accumulation_steps: 2
-- total_train_batch_size: 6
+- total_train_batch_size: 4
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: constant
 - lr_scheduler_warmup_ratio: 0.03
-- num_epochs: 1
+- num_epochs: 40
 
 ### Training results
 
@@ -74,5 +57,5 @@ The following hyperparameters were used during training:
 - PEFT 0.11.1
 - Transformers 4.41.2
 - Pytorch 2.3.0+cu121
-- Datasets 2.19.2
+- Datasets 2.20.0
 - Tokenizers 0.19.1