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t5-small-finetuned-xsum

Text2Text Generation
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t5
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text-generation-inference
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End of training

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  1. README.md +13 -16
  2. model.safetensors +1 -1
  3. runs/Feb17_18-03-12_Ravi-Desktop/events.out.tfevents.1708207408.Ravi-Desktop.21004.3 +2 -2
README.md CHANGED
@@ -16,11 +16,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 2.4256
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- - Rouge1: 19.6262
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- - Rouge2: 3.6874
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- - Rougel: 17.4155
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- - Rougelsum: 17.5472
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  - Gen Len: 19.0
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  ## Model description
@@ -46,23 +46,20 @@ 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: 10
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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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- | 2.8869 | 1.0 | 584 | 2.6152 | 17.1618 | 2.621 | 15.8121 | 15.8907 | 19.0 |
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- | 2.829 | 2.0 | 1168 | 2.5615 | 17.486 | 2.799 | 15.9032 | 15.9821 | 19.0 |
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- | 2.7721 | 3.0 | 1752 | 2.5222 | 18.2742 | 3.0877 | 16.5789 | 16.6729 | 19.0 |
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- | 2.7416 | 4.0 | 2336 | 2.4921 | 18.8283 | 3.362 | 16.858 | 16.9738 | 19.0 |
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- | 2.7063 | 5.0 | 2920 | 2.4690 | 18.6113 | 3.2539 | 16.6872 | 16.7919 | 19.0 |
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- | 2.6686 | 6.0 | 3504 | 2.4528 | 19.2086 | 3.5071 | 17.1746 | 17.2843 | 19.0 |
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- | 2.652 | 7.0 | 4088 | 2.4403 | 19.3553 | 3.5814 | 17.1871 | 17.2981 | 19.0 |
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- | 2.6338 | 8.0 | 4672 | 2.4319 | 19.6779 | 3.6693 | 17.4134 | 17.529 | 19.0 |
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- | 2.6377 | 9.0 | 5256 | 2.4270 | 19.6024 | 3.6557 | 17.3604 | 17.4862 | 19.0 |
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- | 2.6281 | 10.0 | 5840 | 2.4256 | 19.6262 | 3.6874 | 17.4155 | 17.5472 | 19.0 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 2.5786
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+ - Rouge1: 17.6871
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+ - Rouge2: 2.8149
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+ - Rougel: 16.2108
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+ - Rougelsum: 16.2872
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  - Gen Len: 19.0
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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: 7
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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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+ | 3.6995 | 1.0 | 584 | 2.9255 | 15.8217 | 2.0723 | 14.7572 | 14.7712 | 19.0 |
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+ | 3.1556 | 2.0 | 1168 | 2.7584 | 16.4802 | 2.3382 | 15.3252 | 15.3279 | 19.0 |
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+ | 2.9966 | 3.0 | 1752 | 2.6738 | 16.8183 | 2.4782 | 15.5872 | 15.6212 | 19.0 |
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+ | 2.9189 | 4.0 | 2336 | 2.6263 | 17.2365 | 2.6216 | 15.8703 | 15.9484 | 19.0 |
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+ | 2.868 | 5.0 | 2920 | 2.5983 | 17.1636 | 2.6128 | 15.8154 | 15.8974 | 19.0 |
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+ | 2.8187 | 6.0 | 3504 | 2.5832 | 17.6268 | 2.7895 | 16.1651 | 16.2396 | 19.0 |
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+ | 2.8104 | 7.0 | 4088 | 2.5786 | 17.6871 | 2.8149 | 16.2108 | 16.2872 | 19.0 |
 
 
 
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  ### Framework versions
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