Model save

README.md

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+---
+base_model: bert-base-uncased
+library_name: peft
+license: apache-2.0
+metrics:
+- f1
+- accuracy
+- precision
+- recall
+tags:
+- generated_from_trainer
+model-index:
+- name: Bert-v1
+  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. -->
+
+# Bert-v1
+
+This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.4553
+- F1: 0.9691
+- Accuracy: 0.94
+- Precision: 0.94
+- Recall: 1.0
+
+## 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: 0.002
+- train_batch_size: 1
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- training_steps: 10
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | F1     | Accuracy | Precision | Recall |
+|:-------------:|:-----:|:----:|:---------------:|:------:|:--------:|:---------:|:------:|
+| 0.8405        | 0.001 | 1    | 0.3011          | 0.9691 | 0.94     | 0.94      | 1.0    |
+| 0.2944        | 0.002 | 2    | 0.2259          | 0.9691 | 0.94     | 0.94      | 1.0    |
+| 0.0869        | 0.003 | 3    | 0.2497          | 0.9691 | 0.94     | 0.94      | 1.0    |
+| 0.056         | 0.004 | 4    | 0.3000          | 0.9691 | 0.94     | 0.94      | 1.0    |
+| 0.0137        | 0.005 | 5    | 0.3494          | 0.9691 | 0.94     | 0.94      | 1.0    |
+| 0.0028        | 0.006 | 6    | 0.3885          | 0.9691 | 0.94     | 0.94      | 1.0    |
+| 0.0012        | 0.007 | 7    | 0.4171          | 0.9691 | 0.94     | 0.94      | 1.0    |
+| 0.0038        | 0.008 | 8    | 0.4370          | 0.9691 | 0.94     | 0.94      | 1.0    |
+| 0.0049        | 0.009 | 9    | 0.4496          | 0.9691 | 0.94     | 0.94      | 1.0    |
+| 0.0011        | 0.01  | 10   | 0.4553          | 0.9691 | 0.94     | 0.94      | 1.0    |
+
+
+### Framework versions
+
+- PEFT 0.13.0
+- Transformers 4.45.2
+- Pytorch 2.4.1+cu121
+- Datasets 3.0.1
+- Tokenizers 0.20.0

adapter_config.json

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+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "bert-base-uncased",
+  "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": 16,
+  "lora_dropout": 0.05,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": [
+    "classifier",
+    "score"
+  ],
+  "peft_type": "LORA",
+  "r": 8,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "bert.encoder.layer.0.attention.self.value",
+    "bert.encoder.layer.0.intermediate.dense",
+    "bert.encoder.layer.0.attention.self.query",
+    "bert.encoder.layer.0.attention.self.key"
+  ],
+  "task_type": "SEQ_CLS",
+  "use_dora": false,
+  "use_rslora": false
+}

adapter_model.safetensors

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runs/Oct08_10-45-38_f1da90e0ef55/events.out.tfevents.1728384344.f1da90e0ef55.4879.0

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training_args.bin

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