Na0s
/

Llama-3.1-8B-Pruned-4-Layers_LoRA-PEFT-1.0

@@ -1,142 +1,95 @@
 ---
 library_name: transformers
-tags: []
 ---
-# Model Card for Model ID
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 ## Model Details
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-This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
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 ## Environmental Impact
@@ -144,56 +97,9 @@ Use the code below to get started with the model.
 Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
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 ---
 library_name: transformers
+license: apache-2.0
+datasets:
+- berkeley-nest/Nectar
+pipeline_tag: text-generation
+base_model: Na0s/Llama-3.1-8b-Pruned-4-Layers_LoRA-PEFT
 ---
+<a href="https://ibb.co/0Yhg31Q"><img src="https://i.ibb.co/F8gStcn/Model-card-peft-lora.webp" alt="Model-card-peft-lora" align="center"></a>
+# Model Card for Na0s/Llama-3.1-8B-Pruned-4-Layers_LoRA-PEFT-1.0
 ## Model Details
 ### Model Description
+- **Finetuned from model:[Na0s/Llama-3.1-8B-Pruned-4-Layers_LoRA-PEFT]**
 ## Training Details
+# Parameters used for Na0s/Llama-3.1-8B-Pruned-4-Layers_LoRA-PEFT-1.0
+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 = 16,
+    lora_dropout = 0.05,
+    bias = "none",
+    use_gradient_checkpointing = "unsloth",
+    random_state = 3407,
+    use_rslora = False,
+    loftq_config = None,
+)
+trainer = SFTTrainer(
+    model = model,
+    tokenizer = tokenizer,
+    train_dataset = dataset,
+    dataset_text_field = "completion",
+    max_seq_length = max_seq_length,
+    dataset_num_proc = 2,
+    packing = False,
+    args = TrainingArguments(
+        per_device_train_batch_size = 6,
+        gradient_accumulation_steps = 4,
+        warmup_steps = 5,
+        max_steps=5000,
+        learning_rate = 2e-4,
+        fp16 = not is_bfloat16_supported(),
+        bf16 = is_bfloat16_supported(),
+        logging_steps = 1,
+        optim = "adamw_8bit",
+        weight_decay = 0.01,
+        lr_scheduler_type = "linear",
+        seed = 3407,
+        output_dir = "outputs_2",
+        push_to_hub=True,
+        hub_always_push=True,
+    ),
+)
+Dataset: Berkeley-nest/Nectar
 ### Training Data
 <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+[berkeley-nest/Nectar]
 ## Evaluation
+MMLU Pro 0-shot:
+#### Evaluation Data
 <!-- This should link to a Dataset Card if possible. -->
+[TIGER-AI-Lab/MMLU-Pro]
 ## Environmental Impact
 Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+[More