Model save

README.md

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+---
+library_name: peft
+license: cc-by-4.0
+base_model: pczarnik/herbert-base-ner
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+model-index:
+- name: herbert-ner-lora-numbers
+  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. -->
+
+# herbert-ner-lora-numbers
+
+This model is a fine-tuned version of [pczarnik/herbert-base-ner](https://huggingface.co/pczarnik/herbert-base-ner) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0518
+- Precision: 0.5800
+- Recall: 0.7153
+- F1: 0.6406
+
+## 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: 0.0002
+- train_batch_size: 16
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- num_epochs: 5
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|
+| 0.2409        | 1.0   | 649  | 0.0738          | 0.4740    | 0.6183 | 0.5366 |
+| 0.0761        | 2.0   | 1298 | 0.0631          | 0.5253    | 0.6698 | 0.5888 |
+| 0.0658        | 3.0   | 1947 | 0.0550          | 0.5657    | 0.7064 | 0.6283 |
+| 0.0581        | 4.0   | 2596 | 0.0523          | 0.5832    | 0.7153 | 0.6425 |
+| 0.0565        | 5.0   | 3245 | 0.0518          | 0.5800    | 0.7153 | 0.6406 |
+
+
+### Framework versions
+
+- PEFT 0.12.0
+- Transformers 4.50.3
+- Pytorch 2.4.1
+- Datasets 2.21.0
+- Tokenizers 0.21.1

adapter_config.json

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+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "pczarnik/herbert-base-ner",
+  "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": 32,
+  "lora_dropout": 0.1,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": [
+    "classifier",
+    "score"
+  ],
+  "peft_type": "LORA",
+  "r": 16,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "classifier"
+  ],
+  "task_type": "TOKEN_CLS",
+  "use_dora": false,
+  "use_rslora": false
+}

adapter_model.safetensors

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runs/Apr24_14-06-22_laptop-Micha.local/events.out.tfevents.1745496406.laptop-Micha.local.13856.1

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special_tokens_map.json

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+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

tokenizer_config.json

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+  "clean_up_tokenization_spaces": true,
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+  "pad_token": "<pad>",
+  "sep_token": "</s>",
+  "stride": 0,
+  "tokenizer_class": "HerbertTokenizer",
+  "truncation_side": "right",
+  "truncation_strategy": "longest_first",
+  "unk_token": "<unk>"
+}

training_args.bin

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