End of training

README.md

@@ -1,6 +1,6 @@
 ---
-license: apache-2.0
-base_model: distilbert-base-uncased
+license: cc-by-sa-4.0
+base_model: cl-tohoku/bert-base-japanese-whole-word-masking
 tags:
 - generated_from_trainer
 metrics:
@@ -15,10 +15,10 @@ should probably proofread and complete it, then remove this comment. -->
 
 # my_review_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 [cl-tohoku/bert-base-japanese-whole-word-masking](https://huggingface.co/cl-tohoku/bert-base-japanese-whole-word-masking) on the None dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.4664
-- Accuracy: 0.7940
+- Loss: 0.4346
+- Accuracy: 0.9332
 
 ## Model description
 
@@ -43,19 +43,22 @@ The following hyperparameters were used during training:
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- num_epochs: 2
+- num_epochs: 5
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| No log        | 1.0   | 101  | 0.4857          | 0.7996   |
-| No log        | 2.0   | 202  | 0.4664          | 0.7940   |
+| 0.2084        | 1.0   | 678  | 0.2145          | 0.9363   |
+| 0.1852        | 2.0   | 1356 | 0.2198          | 0.9384   |
+| 0.0955        | 3.0   | 2034 | 0.2944          | 0.9362   |
+| 0.0469        | 4.0   | 2712 | 0.3892          | 0.9359   |
+| 0.0318        | 5.0   | 3390 | 0.4346          | 0.9332   |
 
 
 ### Framework versions
 
-- Transformers 4.34.0
-- Pytorch 2.0.1+cu118
-- Datasets 2.14.5
-- Tokenizers 0.14.1
+- Transformers 4.35.2
+- Pytorch 2.1.0+cu118
+- Datasets 2.15.0
+- Tokenizers 0.15.0

model.safetensors

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runs/Nov23_10-14-36_4b70a48305f4/events.out.tfevents.1700734483.4b70a48305f4.34123.0

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