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: CRAFT_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. -->
+
+# CRAFT_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: 0.1043
+- Seqeval classification report:               precision    recall  f1-score   support
+
+       CHEBI       0.71      0.73      0.72       616
+          CL       0.85      0.89      0.87      1740
+         GGP       0.84      0.76      0.80       611
+          GO       0.89      0.90      0.90      3810
+          SO       0.81      0.83      0.82      8854
+       Taxon       0.58      0.60      0.59       284
+
+   micro avg       0.82      0.84      0.83     15915
+   macro avg       0.78      0.79      0.78     15915
+weighted avg       0.82      0.84      0.83     15915
+
+
+## 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                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                  |
+|:-------------:|:-----:|:----:|:---------------:|:--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:|
+| No log        | 1.0   | 347  | 0.1260          |               precision    recall  f1-score   support
+
+       CHEBI       0.66      0.61      0.63       616
+          CL       0.81      0.86      0.83      1740
+         GGP       0.74      0.54      0.63       611
+          GO       0.86      0.89      0.87      3810
+          SO       0.73      0.78      0.76      8854
+       Taxon       0.47      0.57      0.52       284
+
+   micro avg       0.76      0.80      0.78     15915
+   macro avg       0.71      0.71      0.71     15915
+weighted avg       0.76      0.80      0.78     15915
+ |
+| 0.182         | 2.0   | 695  | 0.1089          |               precision    recall  f1-score   support
+
+       CHEBI       0.69      0.74      0.71       616
+          CL       0.84      0.88      0.86      1740
+         GGP       0.83      0.74      0.78       611
+          GO       0.88      0.90      0.89      3810
+          SO       0.79      0.82      0.81      8854
+       Taxon       0.57      0.60      0.58       284
+
+   micro avg       0.81      0.84      0.82     15915
+   macro avg       0.77      0.78      0.77     15915
+weighted avg       0.81      0.84      0.82     15915
+ |
+| 0.0443        | 3.0   | 1041 | 0.1043          |               precision    recall  f1-score   support
+
+       CHEBI       0.71      0.73      0.72       616
+          CL       0.85      0.89      0.87      1740
+         GGP       0.84      0.76      0.80       611
+          GO       0.89      0.90      0.90      3810
+          SO       0.81      0.83      0.82      8854
+       Taxon       0.58      0.60      0.59       284
+
+   micro avg       0.82      0.84      0.83     15915
+   macro avg       0.78      0.79      0.78     15915
+weighted avg       0.82      0.84      0.83     15915
+ |
+
+
+### Framework versions
+
+- Transformers 4.35.2
+- Pytorch 2.1.0+cu118
+- Datasets 2.15.0
+- Tokenizers 0.15.0