Training in progress epoch 2

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: 0.2804
-- Train Accuracy: 0.8901
-- Train F1 M: 0.4898
-- Train Precision M: 0.3778
-- Train Recall M: 0.7488
-- Validation Loss: 0.2824
-- Validation Accuracy: 0.8879
-- Validation F1 M: 0.5567
-- Validation Precision M: 0.4181
-- Validation Recall M: 0.8782
-- Epoch: 1
+- Train Loss: 0.2254
+- Train Accuracy: 0.9128
+- Train F1 M: 0.5069
+- Train Precision M: 0.3838
+- Train Recall M: 0.8028
+- Validation Loss: 0.2388
+- Validation Accuracy: 0.9090
+- Validation F1 M: 0.5468
+- Validation Precision M: 0.4009
+- Validation Recall M: 0.9053
+- Epoch: 2
 
 ## Model description
 
@@ -53,6 +53,7 @@ The following hyperparameters were used during training:
 |:----------:|:--------------:|:----------:|:-----------------:|:--------------:|:---------------:|:-------------------:|:---------------:|:----------------------:|:-------------------:|:-----:|
 | 0.4434     | 0.8014         | 0.4236     | 0.3661            | 0.5865         | 0.2743          | 0.8872              | 0.4964          | 0.3787                 | 0.7644              | 0     |
 | 0.2804     | 0.8901         | 0.4898     | 0.3778            | 0.7488         | 0.2824          | 0.8879              | 0.5567          | 0.4181                 | 0.8782              | 1     |
+| 0.2254     | 0.9128         | 0.5069     | 0.3838            | 0.8028         | 0.2388          | 0.9090              | 0.5468          | 0.4009                 | 0.9053              | 2     |
 
 
 ### Framework versions

tf_model.h5

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
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+oid sha256:aa616b8a6a18826a0f7d77aa3e6ae5675ac9271ba61b015078d8c00e0df5e49c
 size 1341127728