Training complete

README.md

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+---
+library_name: peft
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+base_model: dmis-lab/biobert-v1.1
+model-index:
+- name: cer_model
+  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. -->
+
+# cer_model
+
+This model is a fine-tuned version of [dmis-lab/biobert-v1.1](https://huggingface.co/dmis-lab/biobert-v1.1) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.5164
+- Precision: 0.0
+- Recall: 0.0
+- F1: 0.0
+- Accuracy: 0.9993
+
+## 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
+- num_epochs: 1
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1  | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:---:|:--------:|
+| 0.535         | 1.0   | 141  | 0.5164          | 0.0       | 0.0    | 0.0 | 0.9993   |
+
+
+### Framework versions
+
+- PEFT 0.8.2
+- Transformers 4.37.0
+- Pytorch 2.1.2+cpu
+- Datasets 2.1.0
+- Tokenizers 0.15.1

adapter_config.json

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+  "base_model_name_or_path": "dmis-lab/biobert-v1.1",
+  "bias": "none",
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+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 8,
+  "lora_dropout": 0.1,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 8,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "value_proj",
+    "query_proj"
+  ],
+  "task_type": "TOKEN_CLS",
+  "use_rslora": false
+}

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special_tokens_map.json

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tokenizer_config.json

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+}

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