End of training

README.md

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+---
+base_model: allenai/scibert_scivocab_uncased
+tags:
+- generated_from_trainer
+model-index:
+- name: JNLPBA_SciBERT_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_SciBERT_NER
+
+This model is a fine-tuned version of [allenai/scibert_scivocab_uncased](https://huggingface.co/allenai/scibert_scivocab_uncased) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1472
+- Seqeval classification report:               precision    recall  f1-score   support
+
+         DNA       0.83      0.89      0.86      2106
+         RNA       0.88      0.89      0.88      3516
+   cell_line       0.74      0.80      0.77       526
+   cell_type       0.78      0.83      0.80      1475
+     protein       0.98      0.97      0.98     37428
+
+   micro avg       0.96      0.96      0.96     45051
+   macro avg       0.84      0.87      0.86     45051
+weighted avg       0.96      0.96      0.96     45051
+
+
+## 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                                                                                                                                                                                                                                                                                                                                                                                                                                                                            |
+|:-------------:|:-----:|:----:|:---------------:|:--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:|
+| 0.233         | 1.0   | 582  | 0.1513          |               precision    recall  f1-score   support
+
+         DNA       0.82      0.89      0.85      2106
+         RNA       0.87      0.89      0.88      3516
+   cell_line       0.72      0.79      0.76       526
+   cell_type       0.79      0.78      0.79      1475
+     protein       0.98      0.97      0.98     37428
+
+   micro avg       0.95      0.95      0.95     45051
+   macro avg       0.84      0.87      0.85     45051
+weighted avg       0.95      0.95      0.95     45051
+ |
+| 0.138         | 2.0   | 1164 | 0.1486          |               precision    recall  f1-score   support
+
+         DNA       0.85      0.85      0.85      2106
+         RNA       0.89      0.87      0.88      3516
+   cell_line       0.71      0.80      0.75       526
+   cell_type       0.77      0.82      0.79      1475
+     protein       0.98      0.97      0.98     37428
+
+   micro avg       0.96      0.95      0.95     45051
+   macro avg       0.84      0.86      0.85     45051
+weighted avg       0.96      0.95      0.96     45051
+ |
+| 0.1191        | 3.0   | 1746 | 0.1472          |               precision    recall  f1-score   support
+
+         DNA       0.83      0.89      0.86      2106
+         RNA       0.88      0.89      0.88      3516
+   cell_line       0.74      0.80      0.77       526
+   cell_type       0.78      0.83      0.80      1475
+     protein       0.98      0.97      0.98     37428
+
+   micro avg       0.96      0.96      0.96     45051
+   macro avg       0.84      0.87      0.86     45051
+weighted avg       0.96      0.96      0.96     45051
+ |
+
+
+### Framework versions
+
+- Transformers 4.35.2
+- Pytorch 2.1.0+cu121
+- Datasets 2.15.0
+- Tokenizers 0.15.0