Training complete

README.md

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+---
+license: mit
+base_model: microsoft/biogpt
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: biogpt-adverse-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. -->
+
+# biogpt-adverse-ner
+
+This model is a fine-tuned version of [microsoft/biogpt](https://huggingface.co/microsoft/biogpt) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1600
+- Precision: 0.4255
+- Recall: 0.5280
+- F1: 0.4712
+- Accuracy: 0.9471
+
+## 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: 8
+- eval_batch_size: 8
+- seed: 42
+- 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 | Precision | Recall | F1 | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| No log | 1.0 | 449 | 0.1879 | 0.3350 | 0.3187 | 0.3266 | 0.9329 |
+| 0.2647 | 2.0 | 898 | 0.1653 | 0.3653 | 0.4664 | 0.4097 | 0.9430 |
+| 0.159 | 3.0 | 1347 | 0.1600 | 0.4255 | 0.5280 | 0.4712 | 0.9471 |
+
+
+### Framework versions
+
+- Transformers 4.38.2
+- Pytorch 2.2.1+cu121
+- Datasets 2.18.0
+- Tokenizers 0.15.2