End of training

README.md

@@ -21,7 +21,7 @@ model-index:
     metrics:
     - name: Rouge1
       type: rouge
-      value: 0.38289524455734836
+      value: 0.3869876274946419
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -31,11 +31,11 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [allenai/led-base-16384](https://huggingface.co/allenai/led-base-16384) on the cnn_dailymail dataset.
 It achieves the following results on the evaluation set:
-- Loss: 1.5981
-- Rouge1: 0.3829
-- Rouge2: 0.1704
-- Rougel: 0.2569
-- Rougelsum: 0.3614
+- Loss: 1.5544
+- Rouge1: 0.3870
+- Rouge2: 0.1736
+- Rougel: 0.2599
+- Rougelsum: 0.3653
 
 ## Model description
 
@@ -62,7 +62,8 @@ The following hyperparameters were used during training:
 - total_train_batch_size: 128
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- num_epochs: 6
+- num_epochs: 10
+- mixed_precision_training: Native AMP
 
 ### Training results
 
@@ -94,11 +95,29 @@ The following hyperparameters were used during training:
 | 1.6554        | 5.35  | 12000 | 1.6044          | 0.3817 | 0.1695 | 0.2559 | 0.3605    |
 | 1.6155        | 5.57  | 12500 | 1.6010          | 0.3825 | 0.1700 | 0.2561 | 0.3608    |
 | 1.5863        | 5.8   | 13000 | 1.5981          | 0.3829 | 0.1704 | 0.2569 | 0.3614    |
+| 1.6306        | 6.02  | 13500 | 1.6004          | 0.3831 | 0.1702 | 0.2563 | 0.3618    |
+| 1.6425        | 6.24  | 14000 | 1.5987          | 0.3821 | 0.1698 | 0.2561 | 0.3610    |
+| 1.6863        | 6.46  | 14500 | 1.5876          | 0.3837 | 0.1710 | 0.2569 | 0.3622    |
+| 1.6085        | 6.69  | 15000 | 1.5815          | 0.3836 | 0.1717 | 0.2573 | 0.3621    |
+| 1.6267        | 6.91  | 15500 | 1.5792          | 0.3852 | 0.1722 | 0.2579 | 0.3633    |
+| 1.5637        | 7.13  | 16000 | 1.5768          | 0.3830 | 0.1709 | 0.2568 | 0.3611    |
+| 1.5586        | 7.36  | 16500 | 1.5740          | 0.3833 | 0.1706 | 0.2567 | 0.3617    |
+| 1.5389        | 7.58  | 17000 | 1.5689          | 0.3858 | 0.1729 | 0.2590 | 0.3640    |
+| 1.5694        | 7.8   | 17500 | 1.5645          | 0.3853 | 0.1731 | 0.2589 | 0.3636    |
+| 1.5265        | 8.02  | 18000 | 1.5621          | 0.3871 | 0.1733 | 0.2596 | 0.3654    |
+| 1.5273        | 8.25  | 18500 | 1.5624          | 0.3861 | 0.1726 | 0.2588 | 0.3646    |
+| 1.5148        | 8.47  | 19000 | 1.5602          | 0.3866 | 0.1733 | 0.2592 | 0.3651    |
+| 1.532         | 8.69  | 19500 | 1.5599          | 0.3859 | 0.1732 | 0.2593 | 0.3642    |
+| 1.5113        | 8.92  | 20000 | 1.5602          | 0.3877 | 0.1748 | 0.2606 | 0.3658    |
+| 1.5133        | 9.14  | 20500 | 1.5595          | 0.3855 | 0.1725 | 0.2587 | 0.3637    |
+| 1.4875        | 9.36  | 21000 | 1.5572          | 0.3873 | 0.1741 | 0.2600 | 0.3654    |
+| 1.5038        | 9.59  | 21500 | 1.5557          | 0.3860 | 0.1728 | 0.2590 | 0.3641    |
+| 1.5062        | 9.81  | 22000 | 1.5544          | 0.3870 | 0.1736 | 0.2599 | 0.3653    |
 
 
 ### Framework versions
 
-- Transformers 4.30.2
-- Pytorch 1.13.1
-- Datasets 2.13.0
-- Tokenizers 0.13.3
+- Transformers 4.27.1
+- Pytorch 2.0.0+cu118
+- Datasets 2.10.1
+- Tokenizers 0.13.2

generation_config.json

@@ -8,5 +8,5 @@
   "min_length": 100,
   "no_repeat_ngram_size": 3,
   "pad_token_id": 1,
-  "transformers_version": "4.30.2"
+  "transformers_version": "4.27.1"
 }

pytorch_model.bin

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runs/Aug25_13-30-05_pop-os/events.out.tfevents.1692941410.pop-os.8422.0

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