End of training

README.md

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+---
+library_name: peft
+license: apache-2.0
+base_model: answerdotai/ModernBERT-base
+tags:
+- base_model:adapter:answerdotai/ModernBERT-base
+- lora
+- transformers
+metrics:
+- accuracy
+- matthews_correlation
+- f1
+- precision
+- recall
+model-index:
+- name: peft-modernbert-base
+  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. -->
+
+# peft-modernbert-base
+
+This model is a fine-tuned version of [answerdotai/ModernBERT-base](https://huggingface.co/answerdotai/ModernBERT-base) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0410
+- Accuracy: 0.9887
+- Matthews Correlation: 0.9850
+- F1: 0.9760
+- Precision: 0.9730
+- Recall: 0.9792
+
+## 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: 0.0001
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 32
+- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- num_epochs: 1
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Accuracy | Matthews Correlation | F1     | Precision | Recall |
+|:-------------:|:------:|:----:|:---------------:|:--------:|:--------------------:|:------:|:---------:|:------:|
+| 0.5348        | 0.1977 | 1400 | 0.0968          | 0.9722   | 0.9631               | 0.9568 | 0.9528    | 0.9609 |
+| 0.2975        | 0.3954 | 2800 | 0.0728          | 0.9808   | 0.9745               | 0.9637 | 0.9559    | 0.9725 |
+| 0.2385        | 0.5931 | 4200 | 0.0518          | 0.9865   | 0.9821               | 0.9731 | 0.9685    | 0.9780 |
+| 0.2500        | 0.7908 | 5600 | 0.0443          | 0.9882   | 0.9843               | 0.9752 | 0.9709    | 0.9803 |
+| 0.1968        | 0.9885 | 7000 | 0.0410          | 0.9887   | 0.9850               | 0.9760 | 0.9730    | 0.9792 |
+
+
+### Framework versions
+
+- PEFT 0.18.1
+- Transformers 5.2.0
+- Pytorch 2.10.0+cu128
+- Datasets 4.0.0
+- Tokenizers 0.22.2

adapter_config.json

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+{
+  "alora_invocation_tokens": null,
+  "alpha_pattern": {},
+  "arrow_config": null,
+  "auto_mapping": null,
+  "base_model_name_or_path": "answerdotai/ModernBERT-base",
+  "bias": "none",
+  "corda_config": null,
+  "ensure_weight_tying": false,
+  "eva_config": null,
+  "exclude_modules": null,
+  "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_bias": false,
+  "lora_dropout": 0.1,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": [
+    "classifier",
+    "score"
+  ],
+  "peft_type": "LORA",
+  "peft_version": "0.18.1",
+  "qalora_group_size": 16,
+  "r": 8,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "Wqkv",
+    "Wi",
+    "Wo"
+  ],
+  "target_parameters": null,
+  "task_type": "SEQ_CLS",
+  "trainable_token_indices": null,
+  "use_dora": false,
+  "use_qalora": false,
+  "use_rslora": false
+}

adapter_model.safetensors

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+version https://git-lfs.github.com/spec/v1
+oid sha256:9c4664a7b99624d33a3fa03d1ca035edd00ae98c76cadb4c0b711ae25254ad83
+size 6798480

tokenizer_config.json

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+{
+  "backend": "tokenizers",
+  "bos_token": "[CLS]",
+  "clean_up_tokenization_spaces": true,
+  "cls_token": "[CLS]",
+  "eos_token": "[SEP]",
+  "is_local": false,
+  "mask_token": "[MASK]",
+  "model_input_names": [
+    "input_ids",
+    "attention_mask"
+  ],
+  "model_max_length": 8192,
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "tokenizer_class": "TokenizersBackend",
+  "unk_token": "[UNK]"
+}

training_args.bin

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+size 5265