End of training

README.md

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+---
+license: apache-2.0
+base_model: distilbert-base-uncased
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+- precision
+- recall
+model-index:
+- name: FT_DistilBERT
+  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. -->
+
+# FT_DistilBERT
+
+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: 0.2519
+- Accuracy: 0.8892
+- F1: 0.8892
+- Precision: 0.8904
+- Recall: 0.8900
+
+## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 5
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
+| 0.3172        | 1.0   | 1000 | 0.2984          | 0.8745   | 0.8740 | 0.8772    | 0.8734 |
+| 0.2419        | 2.0   | 2000 | 0.2519          | 0.8892   | 0.8892 | 0.8904    | 0.8900 |
+| 0.2102        | 3.0   | 3000 | 0.2963          | 0.8955   | 0.8955 | 0.8960    | 0.8960 |
+| 0.1679        | 4.0   | 4000 | 0.3012          | 0.9005   | 0.9004 | 0.9007    | 0.9002 |
+| 0.1569        | 5.0   | 5000 | 0.3147          | 0.8958   | 0.8957 | 0.8958    | 0.8956 |
+
+
+### Framework versions
+
+- Transformers 4.37.2
+- Pytorch 2.1.0+cu121
+- Datasets 2.17.1
+- Tokenizers 0.15.2

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