Training in progress epoch 0

README.md

@@ -14,12 +14,12 @@ probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on an unknown dataset.
 It achieves the following results on the evaluation set:
-- Train Loss: 2.4795
-- Train End Logits Accuracy: 0.3625
-- Train Start Logits Accuracy: 0.4065
-- Validation Loss: 1.8676
-- Validation End Logits Accuracy: 0.4746
-- Validation Start Logits Accuracy: 0.5254
+- Train Loss: 5.8944
+- Train End Logits Accuracy: 0.0091
+- Train Start Logits Accuracy: 0.0097
+- Validation Loss: 5.9506
+- Validation End Logits Accuracy: 0.3902
+- Validation Start Logits Accuracy: 0.3902
 - Epoch: 0
 
 ## Model description
@@ -39,14 +39,14 @@ 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': True, 'is_legacy_optimizer': False, 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 21993, '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': True, 'is_legacy_optimizer': False, 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 0.0001, 'decay_steps': 7331, '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}
 - training_precision: float32
 
 ### Training results
 
 | Train Loss | Train End Logits Accuracy | Train Start Logits Accuracy | Validation Loss | Validation End Logits Accuracy | Validation Start Logits Accuracy | Epoch |
 |:----------:|:-------------------------:|:---------------------------:|:---------------:|:------------------------------:|:--------------------------------:|:-----:|
-| 2.4795     | 0.3625                    | 0.4065                      | 1.8676          | 0.4746                         | 0.5254                           | 0     |
+| 5.8944     | 0.0091                    | 0.0097                      | 5.9506          | 0.3902                         | 0.3902                           | 0     |
 
 
 ### Framework versions

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