Training in progress epoch 0

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: 0.0547
-- Train Accuracy: 0.9798
-- Train F1 M: 0.5617
-- Train Precision M: 0.4043
-- Train Recall M: 0.9814
-- Validation Loss: 0.2571
-- Validation Accuracy: 0.9215
-- Validation F1 M: 0.5710
-- Validation Precision M: 0.4102
-- Validation Recall M: 0.9854
-- Epoch: 4
+- Train Loss: 0.6885
+- Train Accuracy: 0.5696
+- Train F1 M: 0.4983
+- Train Precision M: 0.3705
+- Train Recall M: 0.9997
+- Validation Loss: 0.6757
+- Validation Accuracy: 0.5937
+- Validation F1 M: 0.6390
+- Validation Precision M: 0.4063
+- Validation Recall M: 1.7203
+- Epoch: 0
 
 ## Model description
 
@@ -44,23 +44,19 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- optimizer: {'name': 'Adam', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': False, 'is_legacy_optimizer': False, 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 3790, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
+- optimizer: {'name': 'Adam', 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 15160, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
 - training_precision: float32
 
 ### Training results
 
 | Train Loss | Train Accuracy | Train F1 M | Train Precision M | Train Recall M | Validation Loss | Validation Accuracy | Validation F1 M | Validation Precision M | Validation Recall M | Epoch |
 |:----------:|:--------------:|:----------:|:-----------------:|:--------------:|:---------------:|:-------------------:|:---------------:|:----------------------:|:-------------------:|:-----:|
-| 0.3876     | 0.8240         | 0.4634     | 0.3602            | 0.7384         | 0.2283          | 0.9096              | 0.5642          | 0.4130                 | 0.9367              | 0     |
-| 0.1901     | 0.9290         | 0.5345     | 0.3949            | 0.8907         | 0.2162          | 0.9274              | 0.5642          | 0.4060                 | 0.9693              | 1     |
-| 0.1235     | 0.9545         | 0.5556     | 0.4028            | 0.9576         | 0.1969          | 0.9228              | 0.5681          | 0.4118                 | 0.9651              | 2     |
-| 0.0845     | 0.9688         | 0.5596     | 0.4031            | 0.9720         | 0.2147          | 0.9222              | 0.5715          | 0.4109                 | 0.9829              | 3     |
-| 0.0547     | 0.9798         | 0.5617     | 0.4043            | 0.9814         | 0.2571          | 0.9215              | 0.5710          | 0.4102                 | 0.9854              | 4     |
+| 0.6885     | 0.5696         | 0.4983     | 0.3705            | 0.9997         | 0.6757          | 0.5937              | 0.6390          | 0.4063                 | 1.7203              | 0     |
 
 
 ### Framework versions
 
 - Transformers 4.34.1
-- TensorFlow 2.14.0
+- TensorFlow 2.10.0
 - Datasets 2.14.5
 - Tokenizers 0.14.1

tf_model.h5

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