Training complete

README.md

@@ -23,7 +23,7 @@ model-index:
     metrics:
     - name: Rouge1
       type: rouge
-      value: 0.0524
+      value: 0.0899
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -33,11 +33,11 @@ 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 xsum dataset.
 It achieves the following results on the evaluation set:
-- Loss: 8.0085
-- Rouge1: 0.0524
-- Rouge2: 0.0083
-- Rougel: 0.0416
-- Rougelsum: 0.0416
+- Loss: 3.6525
+- Rouge1: 0.0899
+- Rouge2: 0.0226
+- Rougel: 0.0821
+- Rougelsum: 0.0807
 
 ## Model description
 
@@ -57,8 +57,8 @@ More information needed
 
 The following hyperparameters were used during training:
 - learning_rate: 5.6e-05
-- train_batch_size: 32
-- eval_batch_size: 32
+- train_batch_size: 2
+- eval_batch_size: 2
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
@@ -68,14 +68,14 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
 |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
-| No log        | 1.0   | 4    | 12.7017         | 0.0208 | 0.0    | 0.0148 | 0.0148    |
-| No log        | 2.0   | 8    | 10.3879         | 0.0208 | 0.0    | 0.0148 | 0.0148    |
-| 18.6837       | 3.0   | 12   | 9.1367          | 0.0208 | 0.0    | 0.0148 | 0.0148    |
-| 18.6837       | 4.0   | 16   | 8.6067          | 0.0269 | 0.0    | 0.0209 | 0.0209    |
-| 18.6837       | 5.0   | 20   | 8.2033          | 0.0377 | 0.0    | 0.026  | 0.0256    |
-| 15.292        | 6.0   | 24   | 8.1000          | 0.0524 | 0.0083 | 0.0416 | 0.0416    |
-| 15.292        | 7.0   | 28   | 8.0750          | 0.0524 | 0.0083 | 0.0416 | 0.0416    |
-| 15.292        | 8.0   | 32   | 8.0085          | 0.0524 | 0.0083 | 0.0416 | 0.0416    |
+| 18.5949       | 1.0   | 50   | 8.8110          | 0.0298 | 0.0    | 0.0298 | 0.0298    |
+| 10.7742       | 2.0   | 100  | 5.1285          | 0.087  | 0.0087 | 0.0805 | 0.0796    |
+| 7.6938        | 3.0   | 150  | 4.3645          | 0.0684 | 0.0    | 0.0579 | 0.0615    |
+| 6.3393        | 4.0   | 200  | 4.0164          | 0.035  | 0.0    | 0.0355 | 0.035     |
+| 5.9075        | 5.0   | 250  | 3.7881          | 0.0579 | 0.0065 | 0.051  | 0.0528    |
+| 5.7394        | 6.0   | 300  | 3.6971          | 0.0749 | 0.0226 | 0.0733 | 0.0733    |
+| 5.4246        | 7.0   | 350  | 3.6652          | 0.0749 | 0.0226 | 0.0733 | 0.0733    |
+| 5.2963        | 8.0   | 400  | 3.6525          | 0.0899 | 0.0226 | 0.0821 | 0.0807    |
 
 
 ### Framework versions

model.safetensors

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training_args.bin

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