End of training

README.md

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+---
+library_name: peft
+license: apache-2.0
+base_model: distilbert-base-uncased
+tags:
+- base_model:adapter:distilbert-base-uncased
+- lora
+- transformers
+metrics:
+- accuracy
+- precision
+- recall
+- f1
+model-index:
+- name: distilbert-base-category-classifier
+  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. -->
+
+# distilbert-base-category-classifier
+
+This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1482
+- Accuracy: 0.9518
+- Precision: 0.9514
+- Recall: 0.9518
+- F1: 0.9515
+
+## 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: 16
+- eval_batch_size: 16
+- seed: 42
+- 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: 3
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
+| 0.5032        | 1.0   | 1342 | 0.2337          | 0.9277   | 0.9265    | 0.9277 | 0.9267 |
+| 0.1954        | 2.0   | 2684 | 0.1623          | 0.9490   | 0.9487    | 0.9490 | 0.9487 |
+| 0.154         | 3.0   | 4026 | 0.1482          | 0.9518   | 0.9514    | 0.9518 | 0.9515 |
+
+
+### Framework versions
+
+- PEFT 0.17.1
+- Transformers 4.55.4
+- Pytorch 2.8.0+cu126
+- Datasets 4.0.0
+- Tokenizers 0.21.4