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favsbot_filtersort_using_t5_summarization

Text2Text Generation
Transformers
PyTorch
t5
Generated from Trainer
Eval Results
Inference Endpoints
text-generation-inference
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update model card README.md

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@@ -21,7 +21,7 @@ model-index:
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  metrics:
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  - name: Rouge1
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  type: rouge
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- value: 32.9593
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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
@@ -31,12 +31,12 @@ 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 the filter_sort dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.5010
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- - Rouge1: 32.9593
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  - Rouge2: 0.0
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- - Rougel: 32.9003
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- - Rougelsum: 32.912
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- - Gen Len: 18.8571
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  ## Model description
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@@ -61,22 +61,32 @@ 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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  ### 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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- | 2.8747 | 1.0 | 14 | 1.5385 | 37.0233 | 13.0159 | 36.9587 | 18.6477 | 16.8968 |
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- | 2.7176 | 2.0 | 28 | 1.3330 | 49.2393 | 17.2269 | 43.7425 | 43.7607 | 18.8492 |
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- | 2.2966 | 3.0 | 42 | 1.1196 | 49.2516 | 17.2269 | 43.7563 | 43.7706 | 18.8135 |
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- | 2.2855 | 4.0 | 56 | 0.9385 | 49.2508 | 17.2269 | 43.7537 | 43.7695 | 18.8532 |
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- | 2.0585 | 5.0 | 70 | 0.7803 | 49.2508 | 17.2269 | 43.7537 | 43.7695 | 18.8532 |
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- | 1.8702 | 6.0 | 84 | 0.6600 | 32.9618 | 0.0 | 32.9021 | 32.9144 | 18.8492 |
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- | 1.7851 | 7.0 | 98 | 0.5868 | 32.9593 | 0.0 | 32.9003 | 32.912 | 18.8571 |
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- | 1.6443 | 8.0 | 112 | 0.5397 | 32.9593 | 0.0 | 32.9003 | 32.912 | 18.8571 |
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- | 1.7303 | 9.0 | 126 | 0.5117 | 32.9593 | 0.0 | 32.9003 | 32.912 | 18.8571 |
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- | 1.6068 | 10.0 | 140 | 0.5010 | 32.9593 | 0.0 | 32.9003 | 32.912 | 18.8571 |
 
 
 
 
 
 
 
 
 
 
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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: 15.7351
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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 [t5-small](https://huggingface.co/t5-small) on the filter_sort dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 2.3327
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+ - Rouge1: 15.7351
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  - Rouge2: 0.0
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+ - Rougel: 13.4803
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+ - Rougelsum: 13.5134
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+ - Gen Len: 12.6667
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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: 20
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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 | 3.8161 | 14.754 | 0.0 | 12.6197 | 12.6426 | 10.5 |
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+ | 4.8789 | 2.0 | 10 | 3.6423 | 14.754 | 0.0 | 12.6197 | 12.6426 | 10.5 |
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+ | 4.8789 | 3.0 | 15 | 3.4687 | 14.754 | 0.0 | 12.6197 | 12.6426 | 10.5 |
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+ | 4.5407 | 4.0 | 20 | 3.3086 | 14.754 | 0.0 | 12.6197 | 12.6426 | 10.5 |
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+ | 4.5407 | 5.0 | 25 | 3.1726 | 14.754 | 0.0 | 12.6197 | 12.6426 | 10.5 |
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+ | 4.2216 | 6.0 | 30 | 3.0464 | 15.7792 | 0.0 | 13.5134 | 13.5411 | 12.6667 |
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+ | 4.2216 | 7.0 | 35 | 2.9326 | 15.7792 | 0.0 | 13.5134 | 13.5411 | 12.6667 |
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+ | 4.0021 | 8.0 | 40 | 2.8305 | 15.7792 | 0.0 | 13.5134 | 13.5411 | 12.6667 |
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+ | 4.0021 | 9.0 | 45 | 2.7386 | 15.7792 | 0.0 | 13.5134 | 13.5411 | 12.6667 |
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+ | 3.7634 | 10.0 | 50 | 2.6588 | 15.7792 | 0.0 | 13.5134 | 13.5411 | 12.6667 |
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+ | 3.7634 | 11.0 | 55 | 2.5916 | 15.7792 | 0.0 | 13.5134 | 13.5411 | 12.6667 |
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+ | 3.6224 | 12.0 | 60 | 2.5358 | 15.7792 | 0.0 | 13.5134 | 13.5411 | 12.6667 |
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+ | 3.6224 | 13.0 | 65 | 2.4895 | 15.7792 | 0.0 | 13.5134 | 13.5411 | 12.6667 |
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+ | 3.496 | 14.0 | 70 | 2.4486 | 15.7792 | 0.0 | 13.5134 | 13.5411 | 12.6667 |
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+ | 3.496 | 15.0 | 75 | 2.4140 | 15.7792 | 0.0 | 13.5134 | 13.5411 | 12.6667 |
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+ | 3.4157 | 16.0 | 80 | 2.3857 | 15.7351 | 0.0 | 13.4803 | 13.5134 | 12.6667 |
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+ | 3.4157 | 17.0 | 85 | 2.3622 | 15.7351 | 0.0 | 13.4803 | 13.5134 | 12.6667 |
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+ | 3.3964 | 18.0 | 90 | 2.3455 | 15.7351 | 0.0 | 13.4803 | 13.5134 | 12.6667 |
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+ | 3.3964 | 19.0 | 95 | 2.3361 | 15.7351 | 0.0 | 13.4803 | 13.5134 | 12.6667 |
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+ | 3.3502 | 20.0 | 100 | 2.3327 | 15.7351 | 0.0 | 13.4803 | 13.5134 | 12.6667 |
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  ### Framework versions