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: BertAbstractComp
+  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. -->
+
+# BertAbstractComp
+
+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: 0.7130
+- Accuracy: 0.8062
+- Precision: 0.4972
+- Recall: 0.4770
+- F1: 0.4772
+- Top3: 0.9490
+- Top3macro: 0.7051
+
+## 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 |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:------:|:---------:|
+| 0.4172        | 1.0   | 1640 | 0.9578          | 0.7640   | 0.4137    | 0.3973 | 0.3969 | 0.9292 | 0.6189    |
+| 0.4051        | 2.0   | 3280 | 0.7427          | 0.8024   | 0.4759    | 0.4656 | 0.4654 | 0.9430 | 0.6759    |
+| 0.2359        | 3.0   | 4920 | 0.8947          | 0.8015   | 0.4735    | 0.4777 | 0.4654 | 0.9402 | 0.6772    |
+| 0.1543        | 4.0   | 6560 | 0.9402          | 0.8097   | 0.4900    | 0.4890 | 0.4839 | 0.9475 | 0.7062    |
+
+
+### Framework versions
+
+- Transformers 4.41.2
+- Pytorch 2.1.2
+- Datasets 2.2.1
+- Tokenizers 0.19.1

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