Training in progress epoch 0

README.md

@@ -1,5 +1,5 @@
 ---
-base_model: bert-base-chinese
+base_model: AIYIYA/my_html
 tags:
 - generated_from_keras_callback
 model-index:
@@ -12,12 +12,13 @@ probably proofread and complete it, then remove this comment. -->
 
 # AIYIYA/my_html
 
-This model is a fine-tuned version of [bert-base-chinese](https://huggingface.co/bert-base-chinese) on an unknown dataset.
+This model is a fine-tuned version of [AIYIYA/my_html](https://huggingface.co/AIYIYA/my_html) on an unknown dataset.
 It achieves the following results on the evaluation set:
-- Train Loss: 0.4622
-- Validation Loss: 0.4601
-- Train Accuracy: 0.9375
-- Epoch: 4
+- Train Loss: 0.0899
+- Train Accuracy: 0.9755
+- Validation Loss: 0.0023
+- Validation Accuracy: 1.0
+- Epoch: 0
 
 ## Model description
 
@@ -36,18 +37,14 @@ 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': False, 'is_legacy_optimizer': False, 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 10, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_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': False, 'is_legacy_optimizer': False, 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 5e-05, 'decay_steps': 102, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
 - training_precision: float32
 
 ### Training results
 
-| Train Loss | Validation Loss | Train Accuracy | Epoch |
-|:----------:|:---------------:|:--------------:|:-----:|
-| 0.6787     | 0.5949          | 0.75           | 0     |
-| 0.5836     | 0.5508          | 0.8125         | 1     |
-| 0.6074     | 0.5035          | 0.9375         | 2     |
-| 0.5222     | 0.4738          | 0.9375         | 3     |
-| 0.4622     | 0.4601          | 0.9375         | 4     |
+| Train Loss | Train Accuracy | Validation Loss | Validation Accuracy | Epoch |
+|:----------:|:--------------:|:---------------:|:-------------------:|:-----:|
+| 0.0899     | 0.9755         | 0.0023          | 1.0                 | 0     |
 
 
 ### Framework versions

config.json

@@ -1,5 +1,5 @@
 {
-  "_name_or_path": "bert-base-chinese",
+  "_name_or_path": "AIYIYA/my_html",
   "architectures": [
     "BertForSequenceClassification"
   ],

tf_model.h5

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:651ae3f7e89531b0d5c8ae2d137180177b383f500ebcd244542248cb1864acbb
+oid sha256:6b150242f3d2e1c965382592a778f78e04ab2bcc70fd01b56b487fbe6a70ee95
 size 409364760

tokenizer_config.json

@@ -3,11 +3,15 @@
   "cls_token": "[CLS]",
   "do_lower_case": false,
   "mask_token": "[MASK]",
+  "max_length": 512,
   "model_max_length": 512,
   "pad_token": "[PAD]",
   "sep_token": "[SEP]",
+  "stride": 0,
   "strip_accents": null,
   "tokenize_chinese_chars": true,
   "tokenizer_class": "BertTokenizer",
+  "truncation_side": "right",
+  "truncation_strategy": "longest_first",
   "unk_token": "[UNK]"
 }