Update README.md
Browse files
README.md
CHANGED
|
@@ -1,22 +1,64 @@
|
|
| 1 |
---
|
| 2 |
-
base_model:
|
|
|
|
|
|
|
| 3 |
language:
|
| 4 |
- en
|
| 5 |
license: apache-2.0
|
| 6 |
tags:
|
| 7 |
- text-generation-inference
|
| 8 |
- transformers
|
|
|
|
|
|
|
| 9 |
- unsloth
|
| 10 |
- llama
|
| 11 |
- gguf
|
| 12 |
---
|
| 13 |
|
| 14 |
-
|
|
|
|
| 15 |
|
| 16 |
- **Developed by:** student-abdullah
|
| 17 |
- **License:** apache-2.0
|
| 18 |
-
- **Finetuned from model
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 19 |
|
| 20 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 21 |
|
| 22 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
---
|
| 2 |
+
base_model: meta-llama/Llama-3.2-1B
|
| 3 |
+
datasets:
|
| 4 |
+
- student-abdullah/BigPharma_Generic_Q-A_Format_Augemented_Dataset
|
| 5 |
language:
|
| 6 |
- en
|
| 7 |
license: apache-2.0
|
| 8 |
tags:
|
| 9 |
- text-generation-inference
|
| 10 |
- transformers
|
| 11 |
+
- torch
|
| 12 |
+
- trl
|
| 13 |
- unsloth
|
| 14 |
- llama
|
| 15 |
- gguf
|
| 16 |
---
|
| 17 |
|
| 18 |
+
|
| 19 |
+
# Uploaded model
|
| 20 |
|
| 21 |
- **Developed by:** student-abdullah
|
| 22 |
- **License:** apache-2.0
|
| 23 |
+
- **Finetuned from model:** meta-llama/Llama-3.2-1B
|
| 24 |
+
- **Created on:** 8th October, 2024
|
| 25 |
+
|
| 26 |
+
---
|
| 27 |
+
# Acknowledgement
|
| 28 |
+
<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>
|
| 29 |
+
|
| 30 |
+
---
|
| 31 |
+
# Model Description
|
| 32 |
+
This model is fine-tuned from the meta-llama/Llama-3.2-1B base model to enhance its capabilities in generating relevant and accurate responses related to generic medications under the PMBJP scheme. The fine-tuning process included the following hyperparameters:
|
| 33 |
+
|
| 34 |
+
- Fine Tuning Template: Llama Q&A
|
| 35 |
+
- Max Tokens: 1024
|
| 36 |
+
- LoRA Alpha: 4
|
| 37 |
+
- LoRA Rank (r): 256
|
| 38 |
+
- Learning rate: 5e-5
|
| 39 |
+
- Gradient Accumulation Steps: 1
|
| 40 |
+
- Batch Size: 8
|
| 41 |
+
- Quantization: None
|
| 42 |
|
| 43 |
+
---
|
| 44 |
+
# Model Quantitative Performace
|
| 45 |
+
- Training Quantitative Loss: 0.1375 (at final 10rd epoch 9020nd Step)
|
| 46 |
+
|
| 47 |
+
---
|
| 48 |
+
# Limitations
|
| 49 |
+
- Token Limitations: With a max token limit of 512, the model might not handle very long queries or contexts effectively.
|
| 50 |
+
- Training Data Limitations: The model’s performance is contingent on the quality and coverage of the fine-tuning dataset, which may affect its generalizability to different contexts or medications not covered in the dataset.
|
| 51 |
+
- Potential Biases: As with any model fine-tuned on specific data, there may be biases based on the dataset used for training.
|
| 52 |
+
|
| 53 |
+
---
|
| 54 |
+
# Model Performace Evaluation:
|
| 55 |
+
- Evaluation on 1000 Questions based on dataset (to evaluate the finetuned knowledge base)
|
| 56 |
+
- At temperature 0.3
|
| 57 |
+
- Correct Responses: %
|
| 58 |
+
- Incorrect Responses: %
|
| 59 |
|
| 60 |
+
<p align="center">
|
| 61 |
+
<img src="" width="20%" style="display:inline-block;"/>
|
| 62 |
+
<img src="" width="35%" style="display:inline-block;"/>
|
| 63 |
+
<img src="" width="35%" style="display:inline-block;"/>
|
| 64 |
+
</p>
|