update model card README.md

README.md

@@ -1,23 +1,22 @@
 ---
-license: apache-2.0
 tags:
-- generated_from_keras_callback
+- generated_from_trainer
+metrics:
+- accuracy
 model-index:
-- name: NawinCom/my_awesome_model
+- name: my_awesome_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. -->
 
-# NawinCom/my_awesome_model
+# my_awesome_model
 
-This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
+This model was trained from scratch on the None dataset.
 It achieves the following results on the evaluation set:
-- Train Loss: 0.1233
-- Validation Loss: 0.0846
-- Train Accuracy: 0.9649
-- Epoch: 0
+- Loss: 0.1455
+- Accuracy: 0.9582
 
 ## Model description
 
@@ -36,19 +35,29 @@ 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': 10610, '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
+- learning_rate: 2e-05
+- train_batch_size: 16
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 2
 
 ### Training results
 
-| Train Loss | Validation Loss | Train Accuracy | Epoch |
-|:----------:|:---------------:|:--------------:|:-----:|
-| 0.1233     | 0.0846          | 0.9649         | 0     |
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| No log        | 0.09  | 200  | 0.1455          | 0.9582   |
+| No log        | 0.19  | 400  | 0.1849          | 0.9604   |
+| 0.0446        | 0.28  | 600  | 0.1580          | 0.9593   |
+| 0.0446        | 0.38  | 800  | 0.1968          | 0.9545   |
+| 0.0635        | 0.47  | 1000 | 0.1853          | 0.9603   |
+| 0.0635        | 0.57  | 1200 | 0.1476          | 0.9589   |
 
 
 ### Framework versions
 
 - Transformers 4.26.1
-- TensorFlow 2.11.0
+- Pytorch 1.13.1+cu116
 - Datasets 2.10.1
 - Tokenizers 0.13.2