loha_fine_tuned_boolq

README.md

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+---
+license: apache-2.0
+library_name: peft
+tags:
+- generated_from_trainer
+base_model: google-bert/bert-base-uncased
+metrics:
+- accuracy
+- f1
+model-index:
+- name: loha_fine_tuned_boolq
+  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. -->
+
+# loha_fine_tuned_boolq
+
+This model is a fine-tuned version of [google-bert/bert-base-uncased](https://huggingface.co/google-bert/bert-base-uncased) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.5655
+- Accuracy: 0.7778
+- F1: 0.6806
+
+## 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: 2e-05
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- training_steps: 400
+
+### Training results
+
+| Training Loss | Epoch   | Step | Validation Loss | Accuracy | F1     |
+|:-------------:|:-------:|:----:|:---------------:|:--------:|:------:|
+| 0.6686        | 4.1667  | 50   | 0.6058          | 0.7778   | 0.6806 |
+| 0.661         | 8.3333  | 100  | 0.5835          | 0.7778   | 0.6806 |
+| 0.66          | 12.5    | 150  | 0.5765          | 0.7778   | 0.6806 |
+| 0.6685        | 16.6667 | 200  | 0.5708          | 0.7778   | 0.6806 |
+| 0.6634        | 20.8333 | 250  | 0.5677          | 0.7778   | 0.6806 |
+| 0.6573        | 25.0    | 300  | 0.5668          | 0.7778   | 0.6806 |
+| 0.6623        | 29.1667 | 350  | 0.5661          | 0.7778   | 0.6806 |
+| 0.6583        | 33.3333 | 400  | 0.5655          | 0.7778   | 0.6806 |
+
+
+### Framework versions
+
+- PEFT 0.10.1.dev0
+- Transformers 4.40.1
+- Pytorch 2.1.1+cu121
+- Datasets 2.19.0
+- Tokenizers 0.19.1

adapter_config.json

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+{
+  "alpha": 32,
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "google-bert/bert-base-uncased",
+  "inference_mode": true,
+  "init_weights": true,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "module_dropout": 0.0,
+  "modules_to_save": [
+    "classifier",
+    "score"
+  ],
+  "peft_type": "LOHA",
+  "r": 16,
+  "rank_dropout": 0.0,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "query",
+    "value"
+  ],
+  "task_type": "SEQ_CLS",
+  "use_effective_conv2d": false
+}

adapter_model.safetensors

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runs/May03_16-33-32_DESKTOP-22QTFDR/events.out.tfevents.1714746814.DESKTOP-22QTFDR.480.8

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runs/May03_16-33-32_DESKTOP-22QTFDR/events.out.tfevents.1714746950.DESKTOP-22QTFDR.480.9

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special_tokens_map.json

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+{
+  "cls_token": "[CLS]",
+  "mask_token": "[MASK]",
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "unk_token": "[UNK]"
+}

tokenizer_config.json

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+{
+  "added_tokens_decoder": {
+    "0": {
+      "content": "[PAD]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "100": {
+      "content": "[UNK]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "101": {
+      "content": "[CLS]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
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+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
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+      "special": true
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+    "103": {
+      "content": "[MASK]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
+  },
+  "clean_up_tokenization_spaces": true,
+  "cls_token": "[CLS]",
+  "do_lower_case": true,
+  "mask_token": "[MASK]",
+  "model_max_length": 512,
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "strip_accents": null,
+  "tokenize_chinese_chars": true,
+  "tokenizer_class": "BertTokenizer",
+  "unk_token": "[UNK]"
+}

training_args.bin

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