End of training

README.md

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+---
+license: mit
+base_model: microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext
+tags:
+- generated_from_trainer
+model-index:
+- name: JNLPBA_PubMedBERT_NER
+  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. -->
+
+# JNLPBA_PubMedBERT_NER
+
+This model is a fine-tuned version of [microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext](https://huggingface.co/microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1450
+- Seqeval classification report:               precision    recall  f1-score   support
+
+         DNA       0.75      0.83      0.79       955
+         RNA       0.80      0.83      0.82      1144
+   cell_line       0.76      0.79      0.78      5330
+   cell_type       0.86      0.91      0.88      2518
+     protein       0.87      0.85      0.86       926
+
+   micro avg       0.80      0.83      0.81     10873
+   macro avg       0.81      0.84      0.82     10873
+weighted avg       0.80      0.83      0.81     10873
+
+
+## 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
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 32
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 3
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Seqeval classification report                                                                                                                                                                                                                                                                                                                                                                                                                                                                            |
+|:-------------:|:-----:|:----:|:---------------:|:--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:|
+| 0.2726        | 1.0   | 582  | 0.1526          |               precision    recall  f1-score   support
+
+         DNA       0.73      0.82      0.77       955
+         RNA       0.79      0.82      0.81      1144
+   cell_line       0.75      0.78      0.76      5330
+   cell_type       0.86      0.86      0.86      2518
+     protein       0.86      0.84      0.85       926
+
+   micro avg       0.79      0.81      0.80     10873
+   macro avg       0.80      0.82      0.81     10873
+weighted avg       0.79      0.81      0.80     10873
+ |
+| 0.145         | 2.0   | 1164 | 0.1473          |               precision    recall  f1-score   support
+
+         DNA       0.73      0.82      0.77       955
+         RNA       0.85      0.78      0.81      1144
+   cell_line       0.77      0.78      0.78      5330
+   cell_type       0.85      0.92      0.88      2518
+     protein       0.88      0.83      0.85       926
+
+   micro avg       0.80      0.82      0.81     10873
+   macro avg       0.81      0.83      0.82     10873
+weighted avg       0.80      0.82      0.81     10873
+ |
+| 0.1276        | 3.0   | 1746 | 0.1450          |               precision    recall  f1-score   support
+
+         DNA       0.75      0.83      0.79       955
+         RNA       0.80      0.83      0.82      1144
+   cell_line       0.76      0.79      0.78      5330
+   cell_type       0.86      0.91      0.88      2518
+     protein       0.87      0.85      0.86       926
+
+   micro avg       0.80      0.83      0.81     10873
+   macro avg       0.81      0.84      0.82     10873
+weighted avg       0.80      0.83      0.81     10873
+ |
+
+
+### Framework versions
+
+- Transformers 4.35.2
+- Pytorch 2.1.0+cu118
+- Datasets 2.15.0
+- Tokenizers 0.15.0