End of training

README.md

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+---
+license: mit
+base_model: microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract-fulltext
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: Fine_tune_PubMedBert
+  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. -->
+
+# Fine_tune_PubMedBert
+
+This model is a fine-tuned version of [microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract-fulltext](https://huggingface.co/microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract-fulltext) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.4669
+- Precision: 0.6359
+- Recall: 0.7044
+- F1: 0.6684
+- Accuracy: 0.8802
+
+## 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: 5e-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 |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| No log        | 1.0   | 11   | 0.8690          | 0.3548    | 0.0401 | 0.0721 | 0.7691   |
+| No log        | 2.0   | 22   | 0.6036          | 0.6005    | 0.4635 | 0.5232 | 0.8468   |
+| No log        | 3.0   | 33   | 0.4788          | 0.6160    | 0.5912 | 0.6034 | 0.8678   |
+| No log        | 4.0   | 44   | 0.4621          | 0.5331    | 0.6898 | 0.6014 | 0.8611   |
+| No log        | 5.0   | 55   | 0.4319          | 0.5795    | 0.6916 | 0.6306 | 0.8681   |
+| No log        | 6.0   | 66   | 0.4444          | 0.5754    | 0.7099 | 0.6356 | 0.8694   |
+| No log        | 7.0   | 77   | 0.4472          | 0.6069    | 0.7099 | 0.6543 | 0.8756   |
+| No log        | 8.0   | 88   | 0.4556          | 0.6227    | 0.6898 | 0.6545 | 0.8786   |
+| No log        | 9.0   | 99   | 0.4613          | 0.6118    | 0.7190 | 0.6611 | 0.8767   |
+| No log        | 10.0  | 110  | 0.4669          | 0.6359    | 0.7044 | 0.6684 | 0.8802   |
+
+
+### Framework versions
+
+- Transformers 4.35.2
+- Pytorch 2.1.0+cu118
+- Datasets 2.15.0
+- Tokenizers 0.15.0

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runs/Dec09_12-24-11_4e052a4b0b10/events.out.tfevents.1702124652.4e052a4b0b10.558.0

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