Update README.md

README.md

@@ -14,7 +14,6 @@ datasets:
 - yahma/alpaca-cleaned
 - ravithejads/samvaad-hi-filtered
 - HydraIndicLM/hindi_alpaca_dolly_67k
-pipeline_tag: text-generation
 ---
 
 # TinyLlama-1.1B-Hinglish-LORA-v1.0 model
@@ -22,6 +21,66 @@ pipeline_tag: text-generation
 - **Developed by:** [Kiran Kunapuli](https://www.linkedin.com/in/kirankunapuli/)
 - **License:** apache-2.0
 - **Finetuned from model :** unsloth/gemma-2b-bnb-4bit
+- - **Model config:**
+  ```python
+    model = FastLanguageModel.get_peft_model(
+    model,
+    r = 16, 
+    target_modules = ["q_proj", "k_proj", "v_proj", "o_proj",
+                      "gate_proj", "up_proj", "down_proj",],
+    lora_alpha = 32,
+    lora_dropout = 0, 
+    bias = "none",   
+    use_gradient_checkpointing = True, 
+    random_state = 42,
+    use_rslora = True,  
+    loftq_config = None, 
+    )
+  ```
+- **Training parameters:**
+  ```python
+    trainer = SFTTrainer(
+    model = model,
+    tokenizer = tokenizer,
+    train_dataset = dataset,
+    dataset_text_field = "text",
+    max_seq_length = max_seq_length,
+    dataset_num_proc = 2,
+    packing = True,
+    args = TrainingArguments(
+        per_device_train_batch_size = 2,
+        gradient_accumulation_steps = 4,
+        warmup_steps = 5,
+        max_steps = 120,
+        learning_rate = 2e-4,
+        fp16 = not torch.cuda.is_bf16_supported(),
+        bf16 = torch.cuda.is_bf16_supported(),
+        logging_steps = 1,
+        optim = "adamw_8bit",
+        weight_decay = 0.01,
+        lr_scheduler_type = "linear",
+        seed = 42,
+        output_dir = "outputs",
+        report_to = "wandb",
+      ),
+    )
+  ```
+- **Training details:**
+  ```
+  ==((====))==  Unsloth - 2x faster free finetuning | Num GPUs = 1
+     \\   /|    Num examples = 14,343 | Num Epochs = 1
+  O^O/ \_/ \    Batch size per device = 2 | Gradient Accumulation steps = 4
+  \        /    Total batch size = 8 | Total steps = 120
+   "-____-"     Number of trainable parameters = 19,611,648
+
+  GPU = Tesla T4. Max memory = 14.748 GB.
+  2118.7553 seconds used for training.
+  35.31 minutes used for training.
+  Peak reserved memory = 9.172 GB.
+  Peak reserved memory for training = 6.758 GB.
+  Peak reserved memory % of max memory = 62.191 %.
+  Peak reserved memory for training % of max memory = 45.823 %.
+  ```
 
 This gemma model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.