End of training

README.md

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+---
+license: apache-2.0
+base_model: bert-base-uncased
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- precision
+- recall
+- f1
+model-index:
+- name: BertALL
+  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. -->
+
+# BertALL
+
+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: 0.4437
+- Accuracy: 0.8846
+- Precision: 0.8048
+- Recall: 0.8186
+- F1: 0.8105
+- Top3: 0.9828
+- Top3macro: 0.9607
+
+## 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: 4
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Accuracy | Precision | Recall | F1     | Top3   | Top3macro |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:|:------:|:---------:|
+| 0.5593        | 1.0   | 7566  | 0.5067          | 0.8363   | 0.7252    | 0.6802 | 0.6880 | 0.9642 | 0.9173    |
+| 0.3827        | 2.0   | 15132 | 0.4301          | 0.8662   | 0.7785    | 0.7760 | 0.7727 | 0.9766 | 0.9457    |
+| 0.2735        | 3.0   | 22698 | 0.4170          | 0.8760   | 0.7973    | 0.7949 | 0.7920 | 0.9816 | 0.9577    |
+| 0.2132        | 4.0   | 30264 | 0.4437          | 0.8846   | 0.8048    | 0.8186 | 0.8105 | 0.9828 | 0.9607    |
+
+
+### Framework versions
+
+- Transformers 4.41.2
+- Pytorch 2.1.2
+- Datasets 2.2.1
+- Tokenizers 0.19.1

model.safetensors

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