update model card README.md

README.md

@@ -1,5 +1,4 @@
 ---
-base_model: allenai/scibert_scivocab_uncased
 tags:
 - generated_from_trainer
 metrics:
@@ -17,13 +16,13 @@ should probably proofread and complete it, then remove this comment. -->
 
 # patentClassfication2
 
-This model is a fine-tuned version of [allenai/scibert_scivocab_uncased](https://huggingface.co/allenai/scibert_scivocab_uncased) on the None dataset.
+This model was trained from scratch on the None dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.6359
-- Accuracy: 0.655
-- F1: 0.6955
-- Precision: 0.6304
-- Recall: 0.7756
+- Loss: 0.6212
+- Accuracy: 0.6754
+- F1: 0.7015
+- Precision: 0.6475
+- Recall: 0.7653
 
 ## Model description
 
@@ -42,22 +41,30 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- learning_rate: 1.939963376695812e-05
+- learning_rate: 1.939963e-05
 - train_batch_size: 8
 - eval_batch_size: 8
 - seed: 40
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: cosine
 - lr_scheduler_warmup_ratio: 0.1
-- num_epochs: 3
+- num_epochs: 11
 
 ### Training results
 
-| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
-|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
-| 0.6809        | 1.0   | 500  | 0.6729          | 0.625    | 0.5541 | 0.6997    | 0.4587 |
-| 0.6004        | 2.0   | 1000 | 0.6359          | 0.655    | 0.6955 | 0.6304    | 0.7756 |
-| 0.4696        | 3.0   | 1500 | 0.6658          | 0.675    | 0.6919 | 0.6673    | 0.7185 |
+| Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1     | Precision | Recall |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|
+| 0.6217        | 1.0   | 4438  | 0.6251          | 0.6405   | 0.5425 | 0.7414    | 0.4278 |
+| 0.5918        | 2.0   | 8876  | 0.6212          | 0.6754   | 0.7015 | 0.6475    | 0.7653 |
+| 0.5097        | 3.0   | 13314 | 0.8241          | 0.6748   | 0.6827 | 0.6645    | 0.7020 |
+| 0.4099        | 4.0   | 17752 | 1.0772          | 0.6685   | 0.6810 | 0.6542    | 0.7102 |
+| 0.3342        | 5.0   | 22190 | 1.7059          | 0.6550   | 0.6645 | 0.6446    | 0.6857 |
+| 0.216         | 6.0   | 26628 | 2.1970          | 0.6503   | 0.6529 | 0.6459    | 0.6600 |
+| 0.1214        | 7.0   | 31066 | 2.7215          | 0.6498   | 0.6642 | 0.6360    | 0.6950 |
+| 0.0548        | 8.0   | 35504 | 2.9805          | 0.6515   | 0.6557 | 0.6458    | 0.6658 |
+| 0.0356        | 9.0   | 39942 | 3.2608          | 0.6541   | 0.6560 | 0.6503    | 0.6618 |
+| 0.0284        | 10.0  | 44380 | 3.3810          | 0.6513   | 0.6548 | 0.6461    | 0.6638 |
+| 0.0186        | 11.0  | 48818 | 3.3967          | 0.6514   | 0.6576 | 0.6440    | 0.6717 |
 
 
 ### Framework versions