End of training

README.md

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+---
+language:
+- en
+library_name: peft
+tags:
+- generated_from_trainer
+datasets:
+- GEM/viggo
+base_model: microsoft/phi-2
+model-index:
+- name: phi-2
+  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. -->
+
+# phi-2
+
+This model is a fine-tuned version of [microsoftl](https://huggingface.co/microsoftl) on the GEM/viggo dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2330
+
+## 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: 2.5e-05
+- train_batch_size: 1
+- eval_batch_size: 8
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 4
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 5
+- training_steps: 1000
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss |
+|:-------------:|:-----:|:----:|:---------------:|
+| 1.917         | 0.04  | 50   | 1.4649          |
+| 0.7037        | 0.08  | 100  | 0.4905          |
+| 0.4209        | 0.12  | 150  | 0.3564          |
+| 0.3534        | 0.16  | 200  | 0.3127          |
+| 0.311         | 0.2   | 250  | 0.2940          |
+| 0.2944        | 0.24  | 300  | 0.2798          |
+| 0.2838        | 0.27  | 350  | 0.2710          |
+| 0.2744        | 0.31  | 400  | 0.2634          |
+| 0.2657        | 0.35  | 450  | 0.2577          |
+| 0.2692        | 0.39  | 500  | 0.2513          |
+| 0.263         | 0.43  | 550  | 0.2475          |
+| 0.2664        | 0.47  | 600  | 0.2451          |
+| 0.2535        | 0.51  | 650  | 0.2421          |
+| 0.2594        | 0.55  | 700  | 0.2396          |
+| 0.234         | 0.59  | 750  | 0.2379          |
+| 0.2383        | 0.63  | 800  | 0.2361          |
+| 0.2419        | 0.67  | 850  | 0.2350          |
+| 0.2448        | 0.71  | 900  | 0.2337          |
+| 0.241         | 0.74  | 950  | 0.2332          |
+| 0.219         | 0.78  | 1000 | 0.2330          |
+
+
+### Framework versions
+
+- PEFT 0.7.2.dev0
+- Transformers 4.37.0.dev0
+- Pytorch 2.1.0+cu121
+- Datasets 2.16.1
+- Tokenizers 0.15.0

adapter_config.json

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+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "microsoft/phi-2",
+  "bias": "none",
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 16,
+  "lora_dropout": 0.05,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 8,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "fc1",
+    "Wqkv",
+    "fc2"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_rslora": false
+}

adapter_model.safetensors

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+size 26230352

training_args.bin

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