Training complete

README.md

@@ -0,0 +1,93 @@
+---
+library_name: transformers
+license: mit
+base_model: microsoft/biogpt
+tags:
+- generated_from_trainer
+datasets:
+- ncbi_disease
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: biogpt-gpt2class-finetuned-ner
+  results:
+  - task:
+      name: Token Classification
+      type: token-classification
+    dataset:
+      name: ncbi_disease
+      type: ncbi_disease
+      config: ncbi_disease
+      split: validation
+      args: ncbi_disease
+    metrics:
+    - name: Precision
+      type: precision
+      value: 0.42814070351758793
+    - name: Recall
+      type: recall
+      value: 0.5447570332480819
+    - name: F1
+      type: f1
+      value: 0.47945976364659537
+    - name: Accuracy
+      type: accuracy
+      value: 0.953528887448343
+---
+
+<!-- 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-gpt2class-finetuned-ner
+
+This model is a fine-tuned version of [microsoft/biogpt](https://huggingface.co/microsoft/biogpt) on the ncbi_disease dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1597
+- Precision: 0.4281
+- Recall: 0.5448
+- F1: 0.4795
+- Accuracy: 0.9535
+
+## 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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- num_epochs: 3
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.3371        | 1.0   | 679  | 0.1850          | 0.3182    | 0.4399 | 0.3693 | 0.9424   |
+| 0.1771        | 2.0   | 1358 | 0.1583          | 0.4254    | 0.4962 | 0.4581 | 0.9525   |
+| 0.1085        | 3.0   | 2037 | 0.1597          | 0.4281    | 0.5448 | 0.4795 | 0.9535   |
+
+
+### Framework versions
+
+- Transformers 4.51.2
+- Pytorch 2.1.0+cu121
+- Datasets 3.5.0
+- Tokenizers 0.21.1