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Text2Text Generation
Transformers
Safetensors
bart
Generated from Trainer
Inference Endpoints
Model card Files Community
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End of training

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  1. README.md +29 -11
  2. model.safetensors +1 -1
README.md CHANGED
@@ -17,12 +17,12 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [facebook/bart-large-cnn](https://huggingface.co/facebook/bart-large-cnn) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.9619
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- - Rouge1: 0.3774
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- - Rouge2: 0.1256
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- - Rougel: 0.2607
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- - Rougelsum: 0.2615
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- - Gen Len: 69.9412
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  ## Model description
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@@ -47,17 +47,35 @@ The following hyperparameters were used during training:
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  - seed: 42
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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- - num_epochs: 4
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  - mixed_precision_training: Native AMP
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
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- | No log | 1.0 | 5 | 2.1870 | 0.3207 | 0.0851 | 0.2147 | 0.2132 | 75.6471 |
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- | No log | 2.0 | 10 | 2.0146 | 0.3715 | 0.1267 | 0.2567 | 0.2563 | 68.7059 |
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- | No log | 3.0 | 15 | 1.9649 | 0.3759 | 0.1432 | 0.2809 | 0.2818 | 66.5882 |
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- | No log | 4.0 | 20 | 1.9619 | 0.3774 | 0.1256 | 0.2607 | 0.2615 | 69.9412 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [facebook/bart-large-cnn](https://huggingface.co/facebook/bart-large-cnn) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 5.5472
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+ - Rouge1: 0.3909
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+ - Rouge2: 0.1328
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+ - Rougel: 0.2802
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+ - Rougelsum: 0.2801
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+ - Gen Len: 69.8235
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  ## Model description
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  - seed: 42
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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+ - num_epochs: 100
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  - mixed_precision_training: Native AMP
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
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+ | No log | 1.0 | 5 | 2.6381 | 0.3163 | 0.0838 | 0.2135 | 0.2138 | 72.1176 |
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+ | No log | 2.0 | 10 | 2.4739 | 0.345 | 0.0969 | 0.2372 | 0.2364 | 69.7647 |
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+ | No log | 3.0 | 15 | 2.6011 | 0.3719 | 0.116 | 0.2619 | 0.2605 | 69.7059 |
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+ | No log | 4.0 | 20 | 2.7476 | 0.3769 | 0.1156 | 0.2588 | 0.2572 | 72.9412 |
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+ | No log | 5.0 | 25 | 2.9283 | 0.3812 | 0.1206 | 0.2645 | 0.2625 | 74.4706 |
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+ | No log | 6.0 | 30 | 3.3089 | 0.3722 | 0.1194 | 0.2779 | 0.2769 | 70.1765 |
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+ | No log | 7.0 | 35 | 3.6585 | 0.3802 | 0.1177 | 0.2718 | 0.2719 | 73.2941 |
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+ | No log | 8.0 | 40 | 3.8924 | 0.3764 | 0.1056 | 0.2661 | 0.2651 | 70.8235 |
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+ | No log | 9.0 | 45 | 4.3638 | 0.3677 | 0.1144 | 0.2653 | 0.2634 | 74.0 |
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+ | No log | 10.0 | 50 | 4.5590 | 0.354 | 0.1069 | 0.2491 | 0.2477 | 71.0 |
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+ | No log | 11.0 | 55 | 4.5746 | 0.4103 | 0.1359 | 0.2935 | 0.293 | 72.5882 |
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+ | No log | 12.0 | 60 | 4.9055 | 0.3869 | 0.118 | 0.2705 | 0.2695 | 66.1176 |
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+ | No log | 13.0 | 65 | 5.0987 | 0.3947 | 0.1292 | 0.2713 | 0.2716 | 74.7647 |
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+ | No log | 14.0 | 70 | 5.3199 | 0.3814 | 0.1135 | 0.2839 | 0.2816 | 72.2353 |
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+ | No log | 15.0 | 75 | 5.4462 | 0.4092 | 0.1265 | 0.2896 | 0.29 | 68.0 |
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+ | No log | 16.0 | 80 | 5.4262 | 0.412 | 0.1282 | 0.293 | 0.2932 | 72.0 |
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+ | No log | 17.0 | 85 | 5.4873 | 0.3776 | 0.1051 | 0.2637 | 0.2636 | 68.8824 |
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+ | No log | 18.0 | 90 | 5.6043 | 0.3932 | 0.1106 | 0.2734 | 0.2727 | 67.9412 |
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+ | No log | 19.0 | 95 | 5.7495 | 0.3694 | 0.1075 | 0.2699 | 0.2692 | 69.7647 |
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+ | No log | 20.0 | 100 | 5.6518 | 0.3849 | 0.1109 | 0.2714 | 0.2709 | 65.5882 |
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+ | No log | 21.0 | 105 | 5.4524 | 0.3762 | 0.1101 | 0.2598 | 0.2596 | 64.5294 |
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+ | No log | 22.0 | 110 | 5.5472 | 0.3909 | 0.1328 | 0.2802 | 0.2801 | 69.8235 |
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  ### Framework versions
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