Training in progress epoch 2

README.md

@@ -15,13 +15,13 @@ probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
 It achieves the following results on the evaluation set:
-- Train Loss: 0.0163
-- Validation Loss: 0.0451
-- Train Precision: 0.9275
-- Train Recall: 0.9235
-- Train F1: 0.9255
-- Train Accuracy: 0.9865
-- Epoch: 1
+- Train Loss: 0.0084
+- Validation Loss: 0.0587
+- Train Precision: 0.9185
+- Train Recall: 0.9240
+- Train F1: 0.9213
+- Train Accuracy: 0.9857
+- Epoch: 2
 
 ## Model description
 
@@ -49,6 +49,7 @@ The following hyperparameters were used during training:
 |:----------:|:---------------:|:---------------:|:------------:|:--------:|:--------------:|:-----:|
 | 0.0426     | 0.0401          | 0.9159          | 0.9284       | 0.9221   | 0.9860         | 0     |
 | 0.0163     | 0.0451          | 0.9275          | 0.9235       | 0.9255   | 0.9865         | 1     |
+| 0.0084     | 0.0587          | 0.9185          | 0.9240       | 0.9213   | 0.9857         | 2     |
 
 
 ### Framework versions

logs/train/events.out.tfevents.1701563713.snek.100056.0.v2

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logs/validation/events.out.tfevents.1701565217.snek.100056.1.v2

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metrics_by_entity.txt

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 {"ANIM": {"precision": 0.7207253886010363, "recall": 0.6165780141843972, "f1": 0.6645962732919255, "number": "4512"}, "DIS": {"precision": 0.7083734359961501, "recall": 0.7907601396723073, "f1": 0.7473029572280746, "number": "7446"}, "LOC": {"precision": 0.9684916006615023, "recall": 0.9709424083769633, "f1": 0.969715456011155, "number": "22920"}, "ORG": {"precision": 0.9265191965420798, "recall": 0.943064182194617, "f1": 0.934718481467231, "number": "7728"}, "PER": {"precision": 0.9815356674402179, "recall": 0.9926530612244898, "f1": 0.9870630612348434, "number": "19600"}, "overall_precision": 0.9177249435055221, "overall_recall": 0.9270488377326946, "overall_f1": 0.9223633281085059, "overall_accuracy": 0.9854759246787036}
 {"ANIM": {"precision": 0.6615262949782523, "recall": 0.7415780141843972, "f1": 0.6992685475444096, "number": "4512"}, "DIS": {"precision": 0.7221940071102082, "recall": 0.7639000805801772, "f1": 0.7424618196057956, "number": "7446"}, "LOC": {"precision": 0.9658289718413426, "recall": 0.9742146596858638, "f1": 0.9700036925215578, "number": "22920"}, "ORG": {"precision": 0.9490376795879643, "recall": 0.906055900621118, "f1": 0.9270488547596981, "number": "7728"}, "PER": {"precision": 0.9880746101314851, "recall": 0.9891836734693877, "f1": 0.9886288307582478, "number": "19600"}, "overall_precision": 0.9159437298780391, "overall_recall": 0.9284152654084815, "overall_f1": 0.9221373314492372, "overall_accuracy": 0.9860191071049645}
 {"ANIM": {"precision": 0.7041505791505791, "recall": 0.6467198581560284, "f1": 0.6742144177449169, "number": "4512"}, "DIS": {"precision": 0.7505330490405118, "recall": 0.7563792640343808, "f1": 0.7534448160535118, "number": "7446"}, "LOC": {"precision": 0.9699051926589545, "recall": 0.9730366492146597, "f1": 0.9714683974386897, "number": "22920"}, "ORG": {"precision": 0.9303225806451613, "recall": 0.9329710144927537, "f1": 0.931644915363742, "number": "7728"}, "PER": {"precision": 0.9918141819298066, "recall": 0.9890816326530613, "f1": 0.9904460225821284, "number": "19600"}, "overall_precision": 0.9275081533146049, "overall_recall": 0.9235122013953638, "overall_f1": 0.9255058641577523, "overall_accuracy": 0.9865000138390427}
+{"ANIM": {"precision": 0.689280868385346, "recall": 0.675531914893617, "f1": 0.6823371390194761, "number": "4512"}, "DIS": {"precision": 0.7039173275654891, "recall": 0.7867311308084878, "f1": 0.7430238457635719, "number": "7446"}, "LOC": {"precision": 0.9750974831619993, "recall": 0.9601221640488656, "f1": 0.9675518818149842, "number": "22920"}, "ORG": {"precision": 0.9285530049006964, "recall": 0.9316770186335404, "f1": 0.9301123885802868, "number": "7728"}, "PER": {"precision": 0.992619926199262, "recall": 0.9881632653061224, "f1": 0.9903865821231336, "number": "19600"}, "overall_precision": 0.9185336699798651, "overall_recall": 0.9240266212262482, "overall_f1": 0.9212719579433262, "overall_accuracy": 0.9856812038121949}

tf_model.h5

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