End of training

README.md

@@ -16,12 +16,12 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [malmarjeh/t5-arabic-text-summarization](https://huggingface.co/malmarjeh/t5-arabic-text-summarization) on an unknown dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.0348
-- Rouge1: 0.1242
-- Rouge2: 0.0117
-- Rougel: 0.1244
-- Rougelsum: 0.1241
-- Gen Len: 6.9278
+- Loss: 0.0104
+- Rouge1: 0.1382
+- Rouge2: 0.0187
+- Rougel: 0.1382
+- Rougelsum: 0.1382
+- Gen Len: 18.9404
 
 ## Model description
 
@@ -40,33 +40,33 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- learning_rate: 2e-05
+- learning_rate: 0.0005
 - train_batch_size: 1
 - eval_batch_size: 1
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
 - lr_scheduler_warmup_steps: 100
-- num_epochs: 2
+- num_epochs: 5
 - mixed_precision_training: Native AMP
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
 |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
-| 0.6242        | 0.23  | 500  | 0.0883          | 0.1237 | 0.0117 | 0.1239 | 0.1237    | 5.1787  |
-| 0.5832        | 0.46  | 1000 | 0.0658          | 0.1237 | 0.0117 | 0.1239 | 0.1237    | 5.1787  |
-| 0.5007        | 0.7   | 1500 | 0.0554          | 0.1237 | 0.0117 | 0.1239 | 0.1237    | 5.1787  |
-| 0.4419        | 0.93  | 2000 | 0.0490          | 0.1237 | 0.0117 | 0.1239 | 0.1237    | 6.0018  |
-| 0.3982        | 1.16  | 2500 | 0.0440          | 0.1237 | 0.0117 | 0.1239 | 0.1237    | 5.6931  |
-| 0.3671        | 1.39  | 3000 | 0.0383          | 0.1238 | 0.0117 | 0.1239 | 0.1238    | 5.6588  |
-| 0.3509        | 1.62  | 3500 | 0.0360          | 0.1242 | 0.0117 | 0.1244 | 0.1241    | 6.8249  |
-| 0.3332        | 1.86  | 4000 | 0.0348          | 0.1242 | 0.0117 | 0.1244 | 0.1241    | 6.9278  |
+| 0.0338        | 0.23  | 500  | 0.0175          | 0.1514 | 0.0297 | 0.1511 | 0.1518    | 18.9188 |
+| 0.0566        | 0.46  | 1000 | 0.0161          | 0.1565 | 0.0388 | 0.157  | 0.1573    | 18.9188 |
+| 0.0418        | 0.7   | 1500 | 0.0125          | 0.1372 | 0.0199 | 0.1375 | 0.1379    | 18.8105 |
+| 0.0333        | 0.93  | 2000 | 0.0116          | 0.1443 | 0.0253 | 0.1448 | 0.1448    | 18.8051 |
+| 0.0287        | 1.16  | 2500 | 0.0110          | 0.144  | 0.0192 | 0.1442 | 0.1442    | 19.0    |
+| 0.0247        | 1.39  | 3000 | 0.0096          | 0.1511 | 0.024  | 0.1517 | 0.1518    | 19.0    |
+| 0.0219        | 1.62  | 3500 | 0.0087          | 0.1463 | 0.0241 | 0.1462 | 0.1462    | 18.9747 |
+| 0.021         | 1.86  | 4000 | 0.0104          | 0.1382 | 0.0187 | 0.1382 | 0.1382    | 18.9404 |
 
 
 ### Framework versions
 
 - Transformers 4.39.0.dev0
-- Pytorch 2.1.0+cu121
+- Pytorch 2.2.1+cu121
 - Datasets 2.18.0
 - Tokenizers 0.15.2

model.safetensors

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training_args.bin

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