add model

README.md

@@ -17,7 +17,7 @@ model_index:
     metric:
       name: Accuracy
       type: accuracy
-      value: 0.9327367887894648
+      value: 0.9201755866959311
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -27,11 +27,11 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model was trained from scratch on the None dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.2368
-- Precision: 0.6608
-- Recall: 0.6840
-- F1: 0.6722
-- Accuracy: 0.9327
+- Loss: 0.2828
+- Precision: 0.6044
+- Recall: 0.6218
+- F1: 0.6130
+- Accuracy: 0.9202
 
 ## Model description
 
@@ -51,7 +51,7 @@ More information needed
 
 The following hyperparameters were used during training:
 - learning_rate: 2e-05
-- train_batch_size: 16
+- train_batch_size: 32
 - eval_batch_size: 8
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
@@ -62,7 +62,7 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
-| No log        | 1.0   | 207  | 0.2368          | 0.6608    | 0.6840 | 0.6722 | 0.9327   |
+| No log        | 1.0   | 104  | 0.2828          | 0.6044    | 0.6218 | 0.6130 | 0.9202   |
 
 
 ### Framework versions

pytorch_model.bin

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:85f9b9134aba64e688b0682e0aad0b0d68df1158ee4e8fb9c39991d503933eec
+oid sha256:3a8fd33d7cbfe615d528793a399e04fc4767f2435953fc7c5cb33b18af5b807b
 size 430992881

training_args.bin

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:78294d2d48075cf27e2cb5fda1696f3e39e1515eec74d07bc0e1059b9598c845
+oid sha256:f369911459f2f8b9de2dfab8ade6947539ed13f8f8b527c82ee6519b8962c909
 size 2671