gemma9_on_korean_summary_events

README.md

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+---
+base_model: rtzr/ko-gemma-2-9b-it
+library_name: peft
+license: gemma
+tags:
+- generated_from_trainer
+model-index:
+- name: gemma9_on_korean_summary_events
+  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. -->
+
+# gemma9_on_korean_summary_events
+
+This model is a fine-tuned version of [rtzr/ko-gemma-2-9b-it](https://huggingface.co/rtzr/ko-gemma-2-9b-it) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.4183
+
+## 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: 5e-05
+- train_batch_size: 2
+- eval_batch_size: 2
+- seed: 42
+- gradient_accumulation_steps: 5
+- total_train_batch_size: 10
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 50
+- training_steps: 400
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss |
+|:-------------:|:------:|:----:|:---------------:|
+| 1.5952        | 0.1316 | 20   | 1.0820          |
+| 0.9103        | 0.2632 | 40   | 0.7513          |
+| 0.7022        | 0.3947 | 60   | 0.5833          |
+| 0.5149        | 0.5263 | 80   | 0.4630          |
+| 0.4837        | 0.6579 | 100  | 0.4376          |
+| 0.449         | 0.7895 | 120  | 0.4213          |
+| 0.431         | 0.9211 | 140  | 0.4080          |
+| 0.3811        | 1.0526 | 160  | 0.4000          |
+| 0.3227        | 1.1842 | 180  | 0.3964          |
+| 0.283         | 1.3158 | 200  | 0.3974          |
+| 0.2984        | 1.4474 | 220  | 0.3993          |
+| 0.3102        | 1.5789 | 240  | 0.3851          |
+| 0.3045        | 1.7105 | 260  | 0.3847          |
+| 0.3034        | 1.8421 | 280  | 0.3851          |
+| 0.2779        | 1.9737 | 300  | 0.3793          |
+| 0.2191        | 2.1053 | 320  | 0.3991          |
+| 0.1971        | 2.2368 | 340  | 0.4157          |
+| 0.1908        | 2.3684 | 360  | 0.4209          |
+| 0.1766        | 2.5    | 380  | 0.4190          |
+| 0.1749        | 2.6316 | 400  | 0.4183          |
+
+
+### Framework versions
+
+- PEFT 0.12.0
+- Transformers 4.43.4
+- Pytorch 2.3.1+cu121
+- Datasets 2.20.0
+- Tokenizers 0.19.1

adapter_config.json

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+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "rtzr/ko-gemma-2-9b-it",
+  "bias": "none",
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 32,
+  "lora_dropout": 0.05,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 16,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "k_proj",
+    "down_proj",
+    "gate_proj",
+    "q_proj",
+    "v_proj",
+    "up_proj",
+    "o_proj"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_dora": false,
+  "use_rslora": false
+}

adapter_model.safetensors

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+size 216151256

training_args.bin

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