End of training

README.md

@@ -14,10 +14,10 @@ should probably proofread and complete it, then remove this comment. -->
 
 # test_model
 
-This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
+This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset.
 It achieves the following results on the evaluation set:
-- Loss: 1.4728
-- F1: 0.5831
+- Loss: 1.2432
+- F1: 0.6031
 
 ## Model description
 
@@ -36,23 +36,21 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- learning_rate: 0.0001
-- train_batch_size: 64
+- learning_rate: 5e-05
+- train_batch_size: 32
 - eval_batch_size: 16
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- num_epochs: 5
+- num_epochs: 3
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | F1     |
 |:-------------:|:-----:|:----:|:---------------:|:------:|
-| No log        | 1.0   | 176  | 1.3057          | 0.5639 |
-| 1.5017        | 2.0   | 352  | 1.3862          | 0.5755 |
-| 0.9071        | 3.0   | 528  | 1.4728          | 0.5831 |
-| 0.5925        | 4.0   | 704  | 1.6452          | 0.5738 |
-| 0.3718        | 5.0   | 880  | 1.6950          | 0.5730 |
+| 1.7459        | 1.0   | 351  | 1.2432          | 0.6031 |
+| 1.0147        | 2.0   | 702  | 1.3064          | 0.5944 |
+| 0.7209        | 3.0   | 1053 | 1.3832          | 0.5969 |
 
 
 ### Framework versions

logs/events.out.tfevents.1686802202.ls.3992184.0

@@ -1,3 +1,3 @@
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+oid sha256:ad161c62ada63f1f6c31fe289f1a06fec24ef72597c6abc3ad120a5a062fb7ba
+size 6536

logs/events.out.tfevents.1686802505.ls.3992184.2

@@ -0,0 +1,3 @@
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+size 405

tokenizer_config.json

@@ -8,6 +8,6 @@
   "special_tokens_map_file": null,
   "strip_accents": null,
   "tokenize_chinese_chars": true,
-  "tokenizer_class": "DistilBertTokenizer",
+  "tokenizer_class": "BertTokenizer",
   "unk_token": "[UNK]"
 }