Training in progress epoch 6

README.md

@@ -15,17 +15,17 @@ probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [bert-large-uncased](https://huggingface.co/bert-large-uncased) on an unknown dataset.
 It achieves the following results on the evaluation set:
-- Train Loss: 0.1380
-- Train Accuracy: 0.9497
-- Train F1 M: 0.5359
-- Train Precision M: 0.3956
-- Train Recall M: 0.8898
-- Validation Loss: 0.2205
-- Validation Accuracy: 0.9228
-- Validation F1 M: 0.5506
-- Validation Precision M: 0.4024
-- Validation Recall M: 0.9213
-- Epoch: 5
+- Train Loss: 0.1200
+- Train Accuracy: 0.9569
+- Train F1 M: 0.5414
+- Train Precision M: 0.3981
+- Train Recall M: 0.9034
+- Validation Loss: 0.2290
+- Validation Accuracy: 0.9202
+- Validation F1 M: 0.5513
+- Validation Precision M: 0.4022
+- Validation Recall M: 0.9261
+- Epoch: 6
 
 ## Model description
 
@@ -57,6 +57,7 @@ The following hyperparameters were used during training:
 | 0.1873     | 0.9303         | 0.5203     | 0.3889            | 0.8490         | 0.2200          | 0.9149              | 0.5561          | 0.4075                 | 0.9235              | 3     |
 | 0.1614     | 0.9404         | 0.5316     | 0.3944            | 0.8756         | 0.2188          | 0.9235              | 0.5566          | 0.4080                 | 0.9242              | 4     |
 | 0.1380     | 0.9497         | 0.5359     | 0.3956            | 0.8898         | 0.2205          | 0.9228              | 0.5506          | 0.4024                 | 0.9213              | 5     |
+| 0.1200     | 0.9569         | 0.5414     | 0.3981            | 0.9034         | 0.2290          | 0.9202              | 0.5513          | 0.4022                 | 0.9261              | 6     |
 
 
 ### Framework versions

tf_model.h5

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:7d27c82601705cec272732dd076f3c99c4dbba525062b8944172f392e4473935
+oid sha256:8f172d61347e429d9928f39f2a0eabb61a5c35caa3c5e7d5f90fac284ec0c063
 size 1341127728