Model save

README.md

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+---
+license: llama3
+library_name: peft
+tags:
+- trl
+- sft
+- generated_from_trainer
+base_model: meta-llama/Meta-Llama-3-8B-Instruct
+model-index:
+- name: Llama2-7b-sft-qlora
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# Llama2-7b-sft-qlora
+
+This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 2.5661
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 0.0002
+- train_batch_size: 4
+- eval_batch_size: 8
+- seed: 42
+- distributed_type: multi-GPU
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 8
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 1
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss |
+|:-------------:|:-----:|:----:|:---------------:|
+| 1.4265        | 1.0   | 1    | 2.5661          |
+
+
+### Framework versions
+
+- PEFT 0.11.1
+- Transformers 4.36.2
+- Pytorch 2.1.2+cu121
+- Datasets 2.19.1
+- Tokenizers 0.15.0

adapter_config.json

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+  "peft_type": "LORA",
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+  "target_modules": [
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+    "up_proj",
+    "down_proj",
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+    "gate_proj",
+    "k_proj"
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+  "task_type": "CAUSAL_LM",
+  "use_dora": false,
+  "use_rslora": false
+}

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all_results.json

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+    "train_samples": 4,
+    "train_samples_per_second": 2.02,
+    "train_steps_per_second": 0.505
+}

dataset_dict.json

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