End of training

README.md

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+---
+license: mit
+base_model: microsoft/Phi-3-mini-4k-instruct
+tags:
+- generated_from_trainer
+model-index:
+- name: Phi0503HMA25
+  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. -->
+
+# Phi0503HMA25
+
+This model is a fine-tuned version of [microsoft/Phi-3-mini-4k-instruct](https://huggingface.co/microsoft/Phi-3-mini-4k-instruct) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1634
+
+## 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: 0.0003
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- gradient_accumulation_steps: 16
+- total_train_batch_size: 128
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine_with_restarts
+- lr_scheduler_warmup_steps: 80
+- num_epochs: 3
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss |
+|:-------------:|:-----:|:----:|:---------------:|
+| 4.0223        | 0.09  | 10   | 0.4709          |
+| 0.3011        | 0.18  | 20   | 0.2486          |
+| 0.2562        | 0.27  | 30   | 0.2446          |
+| 0.2326        | 0.36  | 40   | 0.2224          |
+| 0.202         | 0.45  | 50   | 0.1799          |
+| 0.1963        | 0.54  | 60   | 0.1759          |
+| 0.1688        | 0.63  | 70   | 0.1650          |
+| 0.1672        | 0.73  | 80   | 0.1643          |
+| 0.1662        | 0.82  | 90   | 0.1643          |
+| 0.162         | 0.91  | 100  | 0.1629          |
+| 0.1685        | 1.0   | 110  | 0.1642          |
+| 0.163         | 1.09  | 120  | 0.1650          |
+| 0.1658        | 1.18  | 130  | 0.1633          |
+| 0.1738        | 1.27  | 140  | 0.1628          |
+| 0.1671        | 1.36  | 150  | 0.1631          |
+| 0.1606        | 1.45  | 160  | 0.1659          |
+| 0.1645        | 1.54  | 170  | 0.1637          |
+| 0.1639        | 1.63  | 180  | 0.1628          |
+| 0.1646        | 1.72  | 190  | 0.1678          |
+| 0.1655        | 1.81  | 200  | 0.1640          |
+| 0.1661        | 1.9   | 210  | 0.1635          |
+| 0.1627        | 1.99  | 220  | 0.1640          |
+| 0.1632        | 2.08  | 230  | 0.1634          |
+| 0.1605        | 2.18  | 240  | 0.1627          |
+| 0.1605        | 2.27  | 250  | 0.1631          |
+| 0.163         | 2.36  | 260  | 0.1637          |
+| 0.1613        | 2.45  | 270  | 0.1635          |
+| 0.1617        | 2.54  | 280  | 0.1637          |
+| 0.1617        | 2.63  | 290  | 0.1638          |
+| 0.1629        | 2.72  | 300  | 0.1636          |
+| 0.1633        | 2.81  | 310  | 0.1635          |
+| 0.1618        | 2.9   | 320  | 0.1635          |
+| 0.1663        | 2.99  | 330  | 0.1634          |
+
+
+### Framework versions
+
+- Transformers 4.36.0.dev0
+- Pytorch 2.1.2+cu121
+- Datasets 2.14.6
+- Tokenizers 0.14.0

adapter_config.json

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+  "adaptive_ratio_decay": 1.0,
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+  "auto_mapping": null,
+  "base_model_name_or_path": "microsoft/Phi-3-mini-4k-instruct",
+  "bias": "none",
+  "curr_learning": true,
+  "detached_training": true,
+  "dynamic_adapter_pool": true,
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+  "modules_to_save": null,
+  "num_attention_heads": 32,
+  "num_layers": 32,
+  "num_prefix_set": 3,
+  "num_transformer_submodules": 1,
+  "num_virtual_tokens": 30,
+  "number_of_adapter_pre_layer": 8,
+  "ot_diversified_dispatcher": false,
+  "ot_diversified_prefix": false,
+  "peft_type": "PREFIX_MA_LORA",
+  "pool_selective_inference": true,
+  "pool_selective_training": true,
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+  "r": 8,
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+  "simple_hidden_matching": false,
+  "simple_instance_matching": true,
+  "target_modules": [
+    "qkv_proj",
+    "o_proj"
+  ],
+  "task_type": "CAUSAL_LM",
+  "token_dim": 3072
+}

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added_tokens.json

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tokenizer_config.json

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