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: 0.2122
-- Train Accuracy: 0.9203
-- Train F1 M: 0.5400
-- Train Precision M: 0.3991
-- Train Recall M: 0.8908
-- Validation Loss: 0.2049
-- Validation Accuracy: 0.9215
-- Validation F1 M: 0.5529
-- Validation Precision M: 0.4068
-- Validation Recall M: 0.9089
-- Epoch: 1
+- Train Loss: 0.1339
+- Train Accuracy: 0.9523
+- Train F1 M: 0.5559
+- Train Precision M: 0.4041
+- Train Recall M: 0.9513
+- Validation Loss: 0.2110
+- Validation Accuracy: 0.9222
+- Validation F1 M: 0.5681
+- Validation Precision M: 0.4137
+- Validation Recall M: 0.9574
+- Epoch: 2
 
 ## Model description
 
@@ -53,6 +53,7 @@ The following hyperparameters were used during training:
 |:----------:|:--------------:|:----------:|:-----------------:|:--------------:|:---------------:|:-------------------:|:---------------:|:----------------------:|:-------------------:|:-----:|
 | 0.4176     | 0.8080         | 0.4543     | 0.3667            | 0.6857         | 0.2600          | 0.8991              | 0.5567          | 0.4108                 | 0.9084              | 0     |
 | 0.2122     | 0.9203         | 0.5400     | 0.3991            | 0.8908         | 0.2049          | 0.9215              | 0.5529          | 0.4068                 | 0.9089              | 1     |
+| 0.1339     | 0.9523         | 0.5559     | 0.4041            | 0.9513         | 0.2110          | 0.9222              | 0.5681          | 0.4137                 | 0.9574              | 2     |
 
 
 ### Framework versions

tf_model.h5

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
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+oid sha256:d3d428fab915e339586fc6ed9ceb26d0b3e2e2406fcedeee5efc29746d13175d
 size 1341127728