Update README.md

README.md

@@ -1,31 +1,36 @@
 ---
 library_name: peft
+license: apache-2.0
+datasets:
+- adriantheuma/raven-data
+language:
+- en
 ---
 ### Training details 
 
-- Prompt tokenisation: [LlamaTokenizer](https://huggingface.co/docs/transformers/model_doc/llama2#transformers.LlamaTokenizer). 
-- The maximum context length is limited to 1,204.
-- Per device train batch: 1 
-- Gradient accumulation: 128 steps (achieving the equivalent batch_size of 128)
-- Quantisation: 8-bit (
-- Optimiser: adamw
-- Learning_rate: 3 × 10−4
-- warmup_steps: 100
-- epochs: 5
+* Prompt tokenisation: [LlamaTokenizer](https://huggingface.co/docs/transformers/model_doc/llama2#transformers.LlamaTokenizer). 
+* Maximum context length: 1,204 tokens
+* Per device train batch: 1 
+* Gradient accumulation: 128 steps (achieving the equivalent batch_size of 128)
+* Quantisation: 8-bit
+* Optimiser: adamw
+* Learning_rate: 3 × 10−4
+* warmup_steps: 100
+* epochs: 5
 
-- Low Rank Adaptation (LoRA)
-  - rank: 16
-  - alpha: 16
-  - dropout: 0.05
-  - target modules:  q_proj, k_proj, v_proj, and o_proj
+* Low Rank Adaptation (LoRA)
+  * rank: 16
+  * alpha: 16
+  * dropout: 0.05
+  * target modules:  q_proj, k_proj, v_proj, and o_proj
 
 This setup reduces the trainable parameters to 26,214,400 or 0.2% of the base [Llama 2 13B Chat](https://huggingface.co/docs/transformers/model_doc/llama2) model. 
 
 ### Training hardware
 
 This model is trained on commodity hardware equipped with a: 
-- 13th Gen Intel(R) Core(TM) i7-13700KF CPU at 3.40 GHz
-- 64 GB installed RAM
-- NVIDIA GeForce RTX 4090 GPU with 24 GB onboard RAM.
+* 13th Gen Intel(R) Core(TM) i7-13700KF CPU at 3.40 GHz
+* 64 GB installed RAM
+* NVIDIA GeForce RTX 4090 GPU with 24 GB onboard RAM.
 
-The trained model consumed 100 GPU hours during training.
+The trained model consumed 100 GPU hours during training.