Model save

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: distilbert-base-uncased
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+- precision
+- recall
+model-index:
+- name: section-classifier-imrad
+  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. -->
+
+# section-classifier-imrad
+
+This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.6468
+- Accuracy: 0.7598
+- F1: 0.7564
+- Precision: 0.7573
+- Recall: 0.7598
+
+## 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: 32
+- eval_batch_size: 32
+- 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
+- lr_scheduler_warmup_steps: 500
+- num_epochs: 3
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
+|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
+| 1.3710        | 0.0062 | 100  | 1.3340          | 0.5067   | 0.3408 | 0.2567    | 0.5067 |
+| 1.1491        | 0.0123 | 200  | 1.0743          | 0.5225   | 0.3760 | 0.6023    | 0.5225 |
+| 0.8367        | 0.0185 | 300  | 0.8677          | 0.6667   | 0.6398 | 0.6909    | 0.6667 |
+| 0.7613        | 0.0246 | 400  | 0.7893          | 0.7169   | 0.7109 | 0.7136    | 0.7169 |
+| 0.8431        | 0.0308 | 500  | 0.7290          | 0.7371   | 0.7332 | 0.7339    | 0.7371 |
+| 0.7468        | 0.0369 | 600  | 0.7296          | 0.7287   | 0.7262 | 0.7363    | 0.7287 |
+| 0.8184        | 0.0431 | 700  | 0.6854          | 0.7489   | 0.7446 | 0.7525    | 0.7489 |
+| 0.7425        | 0.0492 | 800  | 0.6610          | 0.7540   | 0.7500 | 0.7523    | 0.7540 |
+| 0.7334        | 0.0554 | 900  | 0.6606          | 0.7512   | 0.7522 | 0.7560    | 0.7512 |
+| 0.7213        | 0.0615 | 1000 | 0.6793          | 0.7469   | 0.7402 | 0.7542    | 0.7469 |
+| 0.6383        | 0.0677 | 1100 | 0.6771          | 0.7500   | 0.7394 | 0.7595    | 0.7500 |
+
+
+### Framework versions
+
+- Transformers 5.3.0
+- Pytorch 2.10.0+cu128
+- Datasets 4.6.1
+- Tokenizers 0.22.2

model.safetensors

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