Update README.md

README.md

@@ -22,21 +22,25 @@ pipeline_tag: token-classification
 <!-- 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. -->
 
+## Model description
 # entity-recognition-general-sota-v1-finetuned-ner
 
 This model is a fine-tuned version of [numind/entity-recognition-general-sota-v1](https://huggingface.co/numind/entity-recognition-general-sota-v1) on Babelscape/MultiNerd dataset.
-The dataset if filtered on english language and sampled first 1M on train and 100k on validation.
-further filtered with data containing atleast one tag from labels2ids mentioned below.
-Train data - 131280 items
-Eval data - 16410 items
-It achieves the following results on the evaluation set:
+
+It achieves the following results on the validation set:
 - Loss: 0.0396
 - Precision: 0.9138
 - Recall: 0.9146
 - F1: 0.9142
 - Accuracy: 0.9857
 
-## Model description
+
+## Training and evaluation data
+
+The dataset if filtered on english language and sampled first 1M on train and 100k on validation.
+further filtered with data containing atleast one tag from labels2ids mentioned below.
+Training data - 131280 items
+Validation data - 16410 items
 
 Trained on all tags from the MultiNERD dataset.
 
@@ -74,24 +78,10 @@ labels2ids = {
     "I-VEHI": 30,
   }
 
-## Intended uses & limitations
-
-More information needed
-
-## Training and evaluation data
-
-Evaluation on test set:
-{'eval_loss': 0.02707073651254177,
- 'eval_precision': 0.9378337879893957,
- 'eval_recall': 0.9518034704620784,
- 'eval_f1': 0.9447669917943954,
- 'eval_accuracy': 0.9901678553418342,
- 'eval_runtime': 133.0665,
- 'eval_samples_per_second': 247.305,
- 'eval_steps_per_second': 30.917}
-
 ## Training procedure
 
+HF Trainer module
+
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
@@ -103,12 +93,21 @@ The following hyperparameters were used during training:
 - lr_scheduler_type: linear
 - num_epochs: 1
 
-### Training results
+### Training & Test set evaluation results
 
 | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
 | 0.0323        | 1.0   | 6564 | 0.0396          | 0.9138    | 0.9146 | 0.9142 | 0.9857   |
 
+Evaluation on test set:
+{'eval_loss': 0.02707073651254177,
+ 'eval_precision': 0.9378337879893957,
+ 'eval_recall': 0.9518034704620784,
+ 'eval_f1': 0.9447669917943954,
+ 'eval_accuracy': 0.9901678553418342,
+ 'eval_runtime': 133.0665,
+ 'eval_samples_per_second': 247.305,
+ 'eval_steps_per_second': 30.917}
 
 ### Framework versions