Training in progress epoch 4

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: 0.1136
-- Train Accuracy: 0.9570
-- Train F1 M: 0.5387
-- Train Precision M: 0.3946
-- Train Recall M: 0.9100
-- Validation Loss: 0.2265
-- Validation Accuracy: 0.9228
-- Validation F1 M: 0.5653
-- Validation Precision M: 0.4119
-- Validation Recall M: 0.9501
-- Epoch: 3
+- Train Loss: 0.0832
+- Train Accuracy: 0.9695
+- Train F1 M: 0.5509
+- Train Precision M: 0.4007
+- Train Recall M: 0.9444
+- Validation Loss: 0.2387
+- Validation Accuracy: 0.9248
+- Validation F1 M: 0.5604
+- Validation Precision M: 0.4074
+- Validation Recall M: 0.9461
+- Epoch: 4
 
 ## Model description
 
@@ -55,6 +55,7 @@ The following hyperparameters were used during training:
 | 0.2070     | 0.9228         | 0.4927     | 0.3723            | 0.7869         | 0.1911          | 0.9268              | 0.5222          | 0.3853                 | 0.8520              | 1     |
 | 0.1392     | 0.9467         | 0.5266     | 0.3881            | 0.8670         | 0.2310          | 0.9057              | 0.5617          | 0.4162                 | 0.9092              | 2     |
 | 0.1136     | 0.9570         | 0.5387     | 0.3946            | 0.9100         | 0.2265          | 0.9228              | 0.5653          | 0.4119                 | 0.9501              | 3     |
+| 0.0832     | 0.9695         | 0.5509     | 0.4007            | 0.9444         | 0.2387          | 0.9248              | 0.5604          | 0.4074                 | 0.9461              | 4     |
 
 
 ### Framework versions

tf_model.h5

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
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+oid sha256:a8b832c57fbe567d6565f683967098a199f9c3e4cb8fb92a786c843b8621b310
 size 1341127728