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texasdave2
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flan-t5-base-samsum

Text2Text Generation
Transformers
PyTorch
t5
Generated from Trainer
Eval Results
text-generation-inference
Inference Endpoints
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  1. README.md +29 -29
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@@ -22,7 +22,7 @@ model-index:
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  metrics:
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  - name: Rouge1
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  type: rouge
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- value: 47.08
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -33,10 +33,10 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) on the samsum dataset.
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  It achieves the following results on the evaluation set:
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  - Loss: 1.3859
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- - Rouge1: 47.08
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- - Rouge2: 23.2603
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- - Rougel: 39.2645
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- - Rougelsum: 43.2898
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  - Gen Len: 17.3333
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  ## Model description
@@ -68,30 +68,30 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
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  |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
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- | 1.5121 | 0.08 | 50 | 1.4287 | 46.7443 | 22.8826 | 38.9466 | 42.862 | 16.9634 |
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- | 1.46 | 0.16 | 100 | 1.4199 | 46.7723 | 22.8011 | 39.0224 | 42.9095 | 17.2393 |
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- | 1.4515 | 0.24 | 150 | 1.4147 | 46.6593 | 23.027 | 38.9378 | 42.8492 | 17.1245 |
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- | 1.4679 | 0.33 | 200 | 1.4121 | 46.8312 | 22.8345 | 39.1545 | 43.2035 | 17.3431 |
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- | 1.451 | 0.41 | 250 | 1.4109 | 46.826 | 23.038 | 39.2744 | 43.3106 | 17.2686 |
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- | 1.4434 | 0.49 | 300 | 1.4040 | 46.6744 | 23.0221 | 39.3167 | 43.1835 | 16.9158 |
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- | 1.4417 | 0.57 | 350 | 1.4007 | 46.851 | 23.0448 | 39.2346 | 43.2396 | 17.1172 |
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- | 1.4781 | 0.65 | 400 | 1.3952 | 46.7831 | 23.1146 | 39.295 | 43.2256 | 17.2076 |
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- | 1.4626 | 0.73 | 450 | 1.3940 | 47.0933 | 23.2741 | 39.2954 | 43.3102 | 17.2222 |
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- | 1.4307 | 0.81 | 500 | 1.3955 | 46.8827 | 23.2016 | 39.2817 | 43.2379 | 17.2002 |
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- | 1.4586 | 0.9 | 550 | 1.3933 | 46.7152 | 23.1439 | 39.2576 | 43.1754 | 17.3040 |
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- | 1.4465 | 0.98 | 600 | 1.3905 | 46.8332 | 23.3356 | 39.2596 | 43.2472 | 17.3468 |
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- | 1.381 | 1.06 | 650 | 1.3953 | 46.9289 | 22.9605 | 39.0651 | 43.2085 | 17.4066 |
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- | 1.4125 | 1.14 | 700 | 1.3922 | 46.4822 | 23.0893 | 38.9024 | 42.9789 | 17.2381 |
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- | 1.3667 | 1.22 | 750 | 1.3922 | 47.2977 | 23.4064 | 39.5091 | 43.5742 | 17.2930 |
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- | 1.3878 | 1.3 | 800 | 1.3953 | 46.6405 | 23.2132 | 39.2853 | 43.3049 | 17.3358 |
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- | 1.3884 | 1.38 | 850 | 1.3931 | 46.9152 | 23.1594 | 39.1629 | 43.2254 | 17.3614 |
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- | 1.3766 | 1.47 | 900 | 1.3898 | 46.988 | 23.1708 | 39.2446 | 43.311 | 17.3333 |
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- | 1.3727 | 1.55 | 950 | 1.3889 | 46.6771 | 23.0915 | 39.0787 | 43.0184 | 17.3211 |
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- | 1.4001 | 1.63 | 1000 | 1.3859 | 47.08 | 23.2603 | 39.2645 | 43.2898 | 17.3333 |
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- | 1.3894 | 1.71 | 1050 | 1.3874 | 47.2134 | 23.3696 | 39.4356 | 43.5422 | 17.3297 |
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- | 1.3697 | 1.79 | 1100 | 1.3860 | 47.06 | 23.3769 | 39.3494 | 43.4113 | 17.3504 |
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- | 1.3886 | 1.87 | 1150 | 1.3862 | 47.0159 | 23.3728 | 39.3871 | 43.4016 | 17.3260 |
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- | 1.4037 | 1.95 | 1200 | 1.3861 | 47.0039 | 23.4055 | 39.3356 | 43.3787 | 17.3321 |
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  ### Framework versions
 
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  metrics:
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  - name: Rouge1
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  type: rouge
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+ value: 47.0919
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 
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  This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) on the samsum dataset.
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  It achieves the following results on the evaluation set:
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  - Loss: 1.3859
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+ - Rouge1: 47.0919
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+ - Rouge2: 23.2123
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+ - Rougel: 39.2407
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+ - Rougelsum: 43.2174
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  - Gen Len: 17.3333
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  ## Model description
 
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  | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
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  |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
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+ | 1.5121 | 0.08 | 50 | 1.4287 | 46.7806 | 22.8207 | 38.9302 | 42.7835 | 16.9634 |
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+ | 1.46 | 0.16 | 100 | 1.4199 | 46.826 | 22.7844 | 39.0295 | 42.8573 | 17.2393 |
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+ | 1.4515 | 0.24 | 150 | 1.4147 | 46.6646 | 22.9602 | 38.9391 | 42.8187 | 17.1245 |
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+ | 1.4679 | 0.33 | 200 | 1.4121 | 46.8291 | 22.7922 | 39.1404 | 43.1542 | 17.3431 |
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+ | 1.451 | 0.41 | 250 | 1.4109 | 46.8103 | 23.0066 | 39.2832 | 43.2411 | 17.2686 |
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+ | 1.4434 | 0.49 | 300 | 1.4040 | 46.6321 | 22.989 | 39.3016 | 43.0997 | 16.9158 |
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+ | 1.4417 | 0.57 | 350 | 1.4007 | 46.8538 | 22.9937 | 39.2135 | 43.1728 | 17.1172 |
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+ | 1.4781 | 0.65 | 400 | 1.3952 | 46.8055 | 23.036 | 39.2961 | 43.1755 | 17.2076 |
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+ | 1.4626 | 0.73 | 450 | 1.3940 | 47.0996 | 23.2205 | 39.3007 | 43.2286 | 17.2222 |
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+ | 1.4307 | 0.81 | 500 | 1.3955 | 46.8877 | 23.1402 | 39.2634 | 43.1279 | 17.2002 |
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+ | 1.4586 | 0.9 | 550 | 1.3933 | 46.7191 | 23.1291 | 39.2437 | 43.1183 | 17.3040 |
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+ | 1.4465 | 0.98 | 600 | 1.3905 | 46.8651 | 23.29 | 39.2514 | 43.2025 | 17.3468 |
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+ | 1.381 | 1.06 | 650 | 1.3953 | 46.9166 | 22.9547 | 39.0439 | 43.1589 | 17.4066 |
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+ | 1.4125 | 1.14 | 700 | 1.3922 | 46.5286 | 23.0552 | 38.9056 | 42.9298 | 17.2381 |
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+ | 1.3667 | 1.22 | 750 | 1.3922 | 47.3239 | 23.3549 | 39.4725 | 43.518 | 17.2930 |
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+ | 1.3878 | 1.3 | 800 | 1.3953 | 46.6837 | 23.1602 | 39.2578 | 43.2195 | 17.3358 |
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+ | 1.3884 | 1.38 | 850 | 1.3931 | 46.9537 | 23.0894 | 39.1676 | 43.1687 | 17.3614 |
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+ | 1.3766 | 1.47 | 900 | 1.3898 | 46.9996 | 23.1407 | 39.2222 | 43.237 | 17.3333 |
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+ | 1.3727 | 1.55 | 950 | 1.3889 | 46.6936 | 23.0454 | 39.0579 | 42.9472 | 17.3211 |
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+ | 1.4001 | 1.63 | 1000 | 1.3859 | 47.0919 | 23.2123 | 39.2407 | 43.2174 | 17.3333 |
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+ | 1.3894 | 1.71 | 1050 | 1.3874 | 47.2229 | 23.35 | 39.4333 | 43.4876 | 17.3297 |
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+ | 1.3697 | 1.79 | 1100 | 1.3860 | 47.0872 | 23.3503 | 39.3371 | 43.3444 | 17.3504 |
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+ | 1.3886 | 1.87 | 1150 | 1.3862 | 47.0516 | 23.3487 | 39.3653 | 43.3272 | 17.3260 |
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+ | 1.4037 | 1.95 | 1200 | 1.3861 | 47.05 | 23.3672 | 39.3131 | 43.3233 | 17.3321 |
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  ### Framework versions