End of training

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: 2025-24679-text-distilbert-predictor
+  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. -->
+
+# 2025-24679-text-distilbert-predictor
+
+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: 0.0040
+- Accuracy: 1.0
+- F1: 1.0
+- Precision: 1.0
+- Recall: 1.0
+
+## 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: 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: 5
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1  | Precision | Recall |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---:|:---------:|:------:|
+| 0.006         | 1.0   | 120  | 0.0042          | 1.0      | 1.0 | 1.0       | 1.0    |
+| 0.0014        | 2.0   | 240  | 0.0011          | 1.0      | 1.0 | 1.0       | 1.0    |
+| 0.0008        | 3.0   | 360  | 0.0006          | 1.0      | 1.0 | 1.0       | 1.0    |
+| 0.0005        | 4.0   | 480  | 0.0004          | 1.0      | 1.0 | 1.0       | 1.0    |
+| 0.0005        | 5.0   | 600  | 0.0004          | 1.0      | 1.0 | 1.0       | 1.0    |
+
+
+### Framework versions
+
+- Transformers 4.56.1
+- Pytorch 2.8.0+cu126
+- Datasets 4.0.0
+- Tokenizers 0.22.0

model.safetensors

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