Praise2112/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext-finetuned-ade-v2-classification

README.md

@@ -5,9 +5,23 @@ tags:
 - generated_from_trainer
 datasets:
 - ade_corpus_v2
+metrics:
+- accuracy
 model-index:
 - name: BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext-finetuned-ade-v2-classification
-  results: []
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: ade_corpus_v2
+      type: ade_corpus_v2
+      config: null
+      split: None
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.9610969387755102
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -16,6 +30,9 @@ should probably proofread and complete it, then remove this comment. -->
 # BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext-finetuned-ade-v2-classification
 
 This model is a fine-tuned version of [BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext](https://huggingface.co/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext) on the ade_corpus_v2 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1982
+- Accuracy: 0.9611
 
 ## Model description
 
@@ -42,6 +59,16 @@ The following hyperparameters were used during training:
 - lr_scheduler_type: linear
 - num_epochs: 4
 
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.1657        | 1.0   | 1176 | 0.1405          | 0.9511   |
+| 0.1019        | 2.0   | 2352 | 0.1767          | 0.9575   |
+| 0.055         | 3.0   | 3528 | 0.1982          | 0.9611   |
+| 0.0424        | 4.0   | 4704 | 0.2038          | 0.9605   |
+
+
 ### Framework versions
 
 - Transformers 4.25.1

pytorch_model.bin

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