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README.md

@@ -1,21 +1,29 @@
 ---
+language:
+- de
 license: apache-2.0
-tags:
-- generated_from_keras_callback
 base_model: distilbert-base-uncased
+metrics:
+- precision
+- recall
+- f1
+- accuracy
 model-index:
-- name: naya-model
+- name: Gkumi/naya-model
   results: []
 ---
 
-<!-- This model card has been generated automatically according to the information Keras had access to. You should
-probably proofread and complete it, then remove this comment. -->
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
 
-# naya-model
+# Gkumi/naya-model
 
 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:
-
+- precision: 0.9260
+- recall: 0.9306
+- f1: 0.9283
+- accuracy: 0.9657
 
 ## Model description
 
@@ -34,16 +42,17 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- optimizer: {'name': 'AdamWeightDecay', 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 10875, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}
-- training_precision: float32
-
-### Training results
-
-
+- num_train_epochs: 5
+- train_batch_size: 16
+- eval_batch_size: 32
+- learning_rate: 2e-05
+- weight_decay_rate: 0.01
+- num_warmup_steps: 0
+- fp16: True
 
 ### Framework versions
 
 - Transformers 4.40.0
-- TensorFlow 2.15.0
+- Pytorch 2.2.2+cu121
 - Datasets 2.18.0
 - Tokenizers 0.19.1