update model card README.md

README.md

@@ -1,22 +1,22 @@
 ---
 license: apache-2.0
 tags:
-- generated_from_keras_callback
+- generated_from_trainer
+datasets:
+- imdb
 model-index:
-- name: arunadiraju/distilbert-base-uncased-finetuned-imdb
+- name: distilbert-base-uncased-finetuned-imdb
   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. -->
 
-# arunadiraju/distilbert-base-uncased-finetuned-imdb
+# distilbert-base-uncased-finetuned-imdb
 
-This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
+This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the imdb dataset.
 It achieves the following results on the evaluation set:
-- Train Loss: 2.8448
-- Validation Loss: 2.5635
-- Epoch: 0
+- Loss: 2.4721
 
 ## Model description
 
@@ -35,19 +35,27 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- optimizer: {'name': 'AdamWeightDecay', 'learning_rate': {'class_name': 'WarmUp', 'config': {'initial_learning_rate': 2e-05, 'decay_schedule_fn': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': -688, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, '__passive_serialization__': True}, 'warmup_steps': 1000, 'power': 1.0, '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: mixed_float16
+- learning_rate: 2e-05
+- train_batch_size: 64
+- eval_batch_size: 64
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 3.0
+- mixed_precision_training: Native AMP
 
 ### Training results
 
-| Train Loss | Validation Loss | Epoch |
-|:----------:|:---------------:|:-----:|
-| 2.8448     | 2.5635          | 0     |
+| Training Loss | Epoch | Step | Validation Loss |
+|:-------------:|:-----:|:----:|:---------------:|
+| 2.7086        | 1.0   | 157  | 2.4897          |
+| 2.5796        | 2.0   | 314  | 2.4230          |
+| 2.5269        | 3.0   | 471  | 2.4354          |
 
 
 ### Framework versions
 
 - Transformers 4.28.1
-- TensorFlow 2.12.0
+- Pytorch 2.0.0+cu118
 - Datasets 2.11.0
 - Tokenizers 0.13.3