End of training

README.md

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+---
+license: apache-2.0
+base_model: bert-base-uncased
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+model-index:
+- name: conjunction-classification-finetuned
+  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. -->
+
+# conjunction-classification-finetuned
+
+This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3628
+- Precision: 0.9722
+- Recall: 0.9630
+- F1-score: 0.9659
+
+## 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: 1e-05
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 500
+- num_epochs: 5
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1-score |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:--------:|
+| 1.0373        | 1.0   | 59   | 1.0341          | 0.1154    | 0.3333 | 0.1714   |
+| 1.0096        | 2.0   | 118  | 0.8995          | 0.4697    | 0.5556 | 0.4602   |
+| 0.8291        | 3.0   | 177  | 0.7374          | 0.4833    | 0.6667 | 0.5402   |
+| 0.6212        | 4.0   | 236  | 0.5642          | 0.8246    | 0.6970 | 0.6032   |
+| 0.3968        | 5.0   | 295  | 0.3628          | 0.9722    | 0.9630 | 0.9659   |
+
+
+### Framework versions
+
+- Transformers 4.35.2
+- Pytorch 2.1.0+cu121
+- Datasets 2.16.1
+- Tokenizers 0.15.0

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