End of training

README.md

@@ -15,14 +15,14 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [SCUT-DLVCLab/lilt-roberta-en-base](https://huggingface.co/SCUT-DLVCLab/lilt-roberta-en-base) on an unknown dataset.
 It achieves the following results on the evaluation set:
-- Loss: 1.2229
-- Answer: {'precision': 0.8436781609195402, 'recall': 0.8984088127294981, 'f1': 0.8701837581505631, 'number': 817}
-- Header: {'precision': 0.5858585858585859, 'recall': 0.48739495798319327, 'f1': 0.5321100917431192, 'number': 119}
-- Question: {'precision': 0.8876712328767123, 'recall': 0.9025069637883009, 'f1': 0.8950276243093923, 'number': 1077}
-- Overall Precision: 0.8547
-- Overall Recall: 0.8763
-- Overall F1: 0.8653
-- Overall Accuracy: 0.7896
+- Loss: 0.9790
+- Answer: {'precision': 0.44588344125809437, 'recall': 0.5899632802937577, 'f1': 0.5079030558482612, 'number': 817}
+- Header: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 119}
+- Question: {'precision': 0.6358296622613803, 'recall': 0.8040854224698236, 'f1': 0.7101271012710128, 'number': 1077}
+- Overall Precision: 0.5484
+- Overall Recall: 0.6696
+- Overall F1: 0.6030
+- Overall Accuracy: 0.6457
 
 ## Model description
 
@@ -47,14 +47,11 @@ The following hyperparameters were used during training:
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- training_steps: 250
+- training_steps: 25
 - mixed_precision_training: Native AMP
 
 ### Training results
 
-| Training Loss | Epoch | Step | Validation Loss | Answer                                                                                                   | Header                                                                                                    | Question                                                                                                  | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
-|:-------------:|:-----:|:----:|:---------------:|:--------------------------------------------------------------------------------------------------------:|:---------------------------------------------------------------------------------------------------------:|:---------------------------------------------------------------------------------------------------------:|:-----------------:|:--------------:|:----------:|:----------------:|
-| 0.108         | 10.53 | 200  | 1.2229          | {'precision': 0.8436781609195402, 'recall': 0.8984088127294981, 'f1': 0.8701837581505631, 'number': 817} | {'precision': 0.5858585858585859, 'recall': 0.48739495798319327, 'f1': 0.5321100917431192, 'number': 119} | {'precision': 0.8876712328767123, 'recall': 0.9025069637883009, 'f1': 0.8950276243093923, 'number': 1077} | 0.8547            | 0.8763         | 0.8653     | 0.7896           |
 
 
 ### Framework versions

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