ZhiguangHan
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mt5-small-task1-dataset2

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ZhiguangHan commited on Dec 15, 2023

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@@ -17,8 +17,8 @@ should probably proofread and complete it, then remove this comment. -->
 This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on the None dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.3880
-- Accuracy: 0.182
 ## Model description
@@ -49,23 +49,23 @@ The following hyperparameters were used during training:
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 4.3254        | 1.0   | 250  | 0.7650          | 0.0      |
-| 0.9928        | 2.0   | 500  | 0.6343          | 0.034    |
-| 0.725         | 3.0   | 750  | 0.5447          | 0.114    |
-| 0.6197        | 4.0   | 1000 | 0.5004          | 0.106    |
-| 0.566         | 5.0   | 1250 | 0.4723          | 0.106    |
-| 0.5267        | 6.0   | 1500 | 0.4457          | 0.128    |
-| 0.4978        | 7.0   | 1750 | 0.4222          | 0.144    |
-| 0.4803        | 8.0   | 2000 | 0.4103          | 0.156    |
-| 0.4683        | 9.0   | 2250 | 0.3969          | 0.172    |
-| 0.4583        | 10.0  | 2500 | 0.3931          | 0.178    |
-| 0.4526        | 11.0  | 2750 | 0.3901          | 0.18     |
-| 0.4438        | 12.0  | 3000 | 0.3880          | 0.182    |
 ### Framework versions
 - Transformers 4.35.2
-- Pytorch 2.1.0+cu118
 - Datasets 2.15.0
 - Tokenizers 0.15.0

 This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on the None dataset.
 It achieves the following results on the evaluation set:
+- Loss: 1.1512
+- Accuracy: 0.176
 ## Model description
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 10.1566       | 1.0   | 250  | 2.1729          | 0.012    |
+| 2.7222        | 2.0   | 500  | 1.8375          | 0.004    |
+| 2.2156        | 3.0   | 750  | 1.6780          | 0.068    |
+| 1.9891        | 4.0   | 1000 | 1.4901          | 0.098    |
+| 1.7951        | 5.0   | 1250 | 1.4195          | 0.116    |
+| 1.6179        | 6.0   | 1500 | 1.2971          | 0.136    |
+| 1.5252        | 7.0   | 1750 | 1.2543          | 0.152    |
+| 1.4486        | 8.0   | 2000 | 1.2054          | 0.162    |
+| 1.3957        | 9.0   | 2250 | 1.1865          | 0.182    |
+| 1.3609        | 10.0  | 2500 | 1.1656          | 0.176    |
+| 1.3395        | 11.0  | 2750 | 1.1589          | 0.176    |
+| 1.3295        | 12.0  | 3000 | 1.1512          | 0.176    |
 ### Framework versions
 - Transformers 4.35.2
+- Pytorch 2.1.0+cu121
 - Datasets 2.15.0
 - Tokenizers 0.15.0