Model save

README.md

@@ -5,9 +5,36 @@ tags:
 - generated_from_trainer
 datasets:
 - plod-filtered
+metrics:
+- precision
+- recall
+- f1
+- accuracy
 model-index:
 - name: roberta-large-finetuned-abbr-finetuned-ner
-  results: []
+  results:
+  - task:
+      name: Token Classification
+      type: token-classification
+    dataset:
+      name: plod-filtered
+      type: plod-filtered
+      config: PLODfiltered
+      split: validation
+      args: PLODfiltered
+    metrics:
+    - name: Precision
+      type: precision
+      value: 0.9800350338833268
+    - name: Recall
+      type: recall
+      value: 0.9766733969309696
+    - name: F1
+      type: f1
+      value: 0.9783513277508114
+    - name: Accuracy
+      type: accuracy
+      value: 0.9761728475392376
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -17,16 +44,11 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [surrey-nlp/roberta-large-finetuned-abbr](https://huggingface.co/surrey-nlp/roberta-large-finetuned-abbr) on the plod-filtered dataset.
 It achieves the following results on the evaluation set:
-- eval_loss: 0.0988
-- eval_precision: 0.9704
-- eval_recall: 0.9689
-- eval_f1: 0.9697
-- eval_accuracy: 0.9665
-- eval_runtime: 204.5482
-- eval_samples_per_second: 118.016
-- eval_steps_per_second: 29.504
-- epoch: 2.72
-- step: 76484
+- Loss: 0.0913
+- Precision: 0.9800
+- Recall: 0.9767
+- F1: 0.9784
+- Accuracy: 0.9762
 
 ## Model description
 
@@ -46,13 +68,25 @@ More information needed
 
 The following hyperparameters were used during training:
 - learning_rate: 2e-05
-- train_batch_size: 4
+- train_batch_size: 16
 - eval_batch_size: 4
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
 - num_epochs: 6
 
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.0805        | 0.99  | 7000  | 0.0761          | 0.9762    | 0.9722 | 0.9742 | 0.9720   |
+| 0.0655        | 1.99  | 14000 | 0.0682          | 0.9769    | 0.9748 | 0.9759 | 0.9735   |
+| 0.0469        | 2.98  | 21000 | 0.0718          | 0.9787    | 0.9746 | 0.9767 | 0.9744   |
+| 0.0336        | 3.98  | 28000 | 0.0851          | 0.9800    | 0.9753 | 0.9776 | 0.9753   |
+| 0.0259        | 4.97  | 35000 | 0.0913          | 0.9800    | 0.9767 | 0.9784 | 0.9762   |
+| 0.0197        | 5.97  | 42000 | 0.0948          | 0.9801    | 0.9774 | 0.9787 | 0.9766   |
+
+
 ### Framework versions
 
 - Transformers 4.35.2