Training in progress epoch 0

README.md

@@ -15,10 +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: 0.1502
-- Validation Loss: 0.2003
-- Train Accuracy: 0.9261
-- Epoch: 4
+- Train Loss: 0.4434
+- Train Accuracy: 0.8014
+- Train F1 M: 0.4236
+- Train Precision M: 0.3661
+- Train Recall M: 0.5865
+- Validation Loss: 0.2743
+- Validation Accuracy: 0.8872
+- Validation F1 M: 0.4964
+- Validation Precision M: 0.3787
+- Validation Recall M: 0.7644
+- Epoch: 0
 
 ## Model description
 
@@ -37,23 +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': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 5e-06, 'decay_steps': 5306, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
+- 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': 5e-06, 'decay_steps': 5306, '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}
 - training_precision: float32
 
 ### Training results
 
-| Train Loss | Validation Loss | Train Accuracy | Epoch |
-|:----------:|:---------------:|:--------------:|:-----:|
-| 0.4352     | 0.3162          | 0.8674         | 0     |
-| 0.2723     | 0.2483          | 0.8951         | 1     |
-| 0.2143     | 0.2118          | 0.9149         | 2     |
-| 0.1788     | 0.2106          | 0.9142         | 3     |
-| 0.1502     | 0.2003          | 0.9261         | 4     |
+| 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 |
+|:----------:|:--------------:|:----------:|:-----------------:|:--------------:|:---------------:|:-------------------:|:---------------:|:----------------------:|:-------------------:|:-----:|
+| 0.4434     | 0.8014         | 0.4236     | 0.3661            | 0.5865         | 0.2743          | 0.8872              | 0.4964          | 0.3787                 | 0.7644              | 0     |
 
 
 ### Framework versions
 
 - Transformers 4.34.1
-- TensorFlow 2.12.0
-- Datasets 2.12.0
+- TensorFlow 2.14.0
+- Datasets 2.14.5
 - Tokenizers 0.14.1

tf_model.h5

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