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: TirkNork/sentence_classfication_test
+- name: sentence_classfication_test
   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. -->
 
-# TirkNork/sentence_classfication_test
+# sentence_classfication_test
 
-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 [airesearch/wangchanberta-base-att-spm-uncased](https://huggingface.co/airesearch/wangchanberta-base-att-spm-uncased) on the None dataset.
 It achieves the following results on the evaluation set:
-- Train Loss: 0.6634
-- Validation Loss: 0.6379
-- Train Accuracy: 0.625
-- Epoch: 0
+- Loss: 0.4453
+- Accuracy: 0.8
 
 ## Model description
 
@@ -36,19 +35,38 @@ 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': 7810, '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: 15
 
 ### Training results
 
-| Train Loss | Validation Loss | Train Accuracy | Epoch |
-|:----------:|:---------------:|:--------------:|:-----:|
-| 0.6634     | 0.6379          | 0.625          | 0     |
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| No log        | 1.0   | 10   | 0.5120          | 0.675    |
+| No log        | 2.0   | 20   | 0.4401          | 0.8      |
+| No log        | 3.0   | 30   | 0.3661          | 0.85     |
+| No log        | 4.0   | 40   | 0.3247          | 0.875    |
+| No log        | 5.0   | 50   | 0.3309          | 0.875    |
+| No log        | 6.0   | 60   | 0.3349          | 0.875    |
+| No log        | 7.0   | 70   | 0.3379          | 0.85     |
+| No log        | 8.0   | 80   | 0.3526          | 0.85     |
+| No log        | 9.0   | 90   | 0.3590          | 0.825    |
+| No log        | 10.0  | 100  | 0.3783          | 0.825    |
+| No log        | 11.0  | 110  | 0.4326          | 0.8      |
+| No log        | 12.0  | 120  | 0.4416          | 0.8      |
+| No log        | 13.0  | 130  | 0.4488          | 0.8      |
+| No log        | 14.0  | 140  | 0.4437          | 0.8      |
+| No log        | 15.0  | 150  | 0.4453          | 0.8      |
 
 
 ### Framework versions
 
 - Transformers 4.29.1
-- TensorFlow 2.12.0
+- Pytorch 2.0.0+cu118
 - Datasets 2.12.0
 - Tokenizers 0.13.3