End of training

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: google-bert/bert-base-uncased
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: VF_BERT_ST_1800
+  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. -->
+
+# VF_BERT_ST_1800
+
+This model is a fine-tuned version of [google-bert/bert-base-uncased](https://huggingface.co/google-bert/bert-base-uncased) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1814
+- Precision: 0.8104
+- Recall: 0.8406
+- F1: 0.8252
+- Accuracy: 0.9657
+
+## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 10
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.2052        | 1.0   | 569  | 0.1207          | 0.7731    | 0.8082 | 0.7903 | 0.9622   |
+| 0.0774        | 2.0   | 1138 | 0.1369          | 0.8062    | 0.7998 | 0.8030 | 0.9629   |
+| 0.0507        | 3.0   | 1707 | 0.1351          | 0.8127    | 0.8386 | 0.8254 | 0.9654   |
+| 0.0328        | 4.0   | 2276 | 0.1331          | 0.8005    | 0.8414 | 0.8204 | 0.9658   |
+| 0.0221        | 5.0   | 2845 | 0.1398          | 0.8144    | 0.8429 | 0.8284 | 0.9668   |
+| 0.0157        | 6.0   | 3414 | 0.1481          | 0.8137    | 0.8401 | 0.8267 | 0.9671   |
+| 0.0117        | 7.0   | 3983 | 0.1804          | 0.8110    | 0.8439 | 0.8271 | 0.9650   |
+| 0.0062        | 8.0   | 4552 | 0.1731          | 0.8133    | 0.8434 | 0.8281 | 0.9658   |
+| 0.005         | 9.0   | 5121 | 0.1835          | 0.8100    | 0.8416 | 0.8255 | 0.9660   |
+| 0.0043        | 10.0  | 5690 | 0.1814          | 0.8104    | 0.8406 | 0.8252 | 0.9657   |
+
+
+### Framework versions
+
+- Transformers 4.44.2
+- Pytorch 2.4.0+cu121
+- Datasets 2.21.0
+- Tokenizers 0.19.1

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