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: Phi0503HMA11
+  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. -->
+
+# Phi0503HMA11
+
+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: 0.0603
+
+## 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: 100
+- num_epochs: 3
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss |
+|:-------------:|:-----:|:----:|:---------------:|
+| 4.2519        | 0.09  | 10   | 1.0412          |
+| 0.9414        | 0.18  | 20   | 1.5076          |
+| 0.5581        | 0.27  | 30   | 0.2855          |
+| 0.266         | 0.36  | 40   | 0.2243          |
+| 0.293         | 0.45  | 50   | 0.2186          |
+| 0.2172        | 0.54  | 60   | 0.2198          |
+| 0.2713        | 0.63  | 70   | 0.5296          |
+| 0.2377        | 0.73  | 80   | 0.1799          |
+| 0.1724        | 0.82  | 90   | 0.1653          |
+| 0.1631        | 0.91  | 100  | 0.1642          |
+| 0.1646        | 1.0   | 110  | 3.8048          |
+| 0.8934        | 1.09  | 120  | 0.1709          |
+| 0.4257        | 1.18  | 130  | 2.8704          |
+| 1.0083        | 1.27  | 140  | 0.1904          |
+| 0.9961        | 1.36  | 150  | 1.9067          |
+| 1.3818        | 1.45  | 160  | 0.5005          |
+| 0.5145        | 1.54  | 170  | 0.4971          |
+| 0.3049        | 1.63  | 180  | 0.2280          |
+| 0.2023        | 1.72  | 190  | 0.1794          |
+| 0.1949        | 1.81  | 200  | 0.1813          |
+| 0.1911        | 1.9   | 210  | 0.1823          |
+| 0.1758        | 1.99  | 220  | 0.1767          |
+| 0.1706        | 2.08  | 230  | 0.1721          |
+| 0.1658        | 2.18  | 240  | 0.1620          |
+| 0.1529        | 2.27  | 250  | 0.1515          |
+| 0.1319        | 2.36  | 260  | 0.1138          |
+| 0.0947        | 2.45  | 270  | 0.0714          |
+| 0.068         | 2.54  | 280  | 0.0690          |
+| 0.0705        | 2.63  | 290  | 0.0642          |
+| 0.0653        | 2.72  | 300  | 0.0624          |
+| 0.0634        | 2.81  | 310  | 0.0611          |
+| 0.0632        | 2.9   | 320  | 0.0613          |
+| 0.0634        | 2.99  | 330  | 0.0603          |
+
+
+### 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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+  "allow_empty_lora": true,
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+  "base_model_name_or_path": "microsoft/Phi-3-mini-4k-instruct",
+  "bias": "none",
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+  "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,
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+  "r": 8,
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+  "simple_hidden_matching": false,
+  "simple_instance_matching": true,
+  "target_modules": [
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+    "o_proj"
+  ],
+  "task_type": "CAUSAL_LM",
+  "token_dim": 3072
+}

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added_tokens.json

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special_tokens_map.json

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tokenizer_config.json

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