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hftest2242
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my_awesome_billsum_model

Text2Text Generation
Transformers
PyTorch
t5
Generated from Trainer
Eval Results
Inference Endpoints
text-generation-inference
Model card Files Community
hftest2242 commited on
Commit
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End of training

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Files changed (2) hide show
  1. README.md +12 -12
  2. pytorch_model.bin +1 -1
README.md CHANGED
@@ -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: 0.1404
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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
@@ -32,11 +32,11 @@ 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 the billsum dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 2.4980
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- - Rouge1: 0.1404
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- - Rouge2: 0.052
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- - Rougel: 0.1172
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- - Rougelsum: 0.1176
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  - Gen Len: 19.0
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  ## Model description
@@ -57,8 +57,8 @@ More information needed
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  The following hyperparameters were used during training:
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  - learning_rate: 2e-05
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- - train_batch_size: 16
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- - eval_batch_size: 16
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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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  | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
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- | No log | 1.0 | 62 | 2.7839 | 0.1277 | 0.0381 | 0.1076 | 0.1081 | 19.0 |
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- | No log | 2.0 | 124 | 2.5780 | 0.1333 | 0.0433 | 0.1114 | 0.1118 | 19.0 |
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- | No log | 3.0 | 186 | 2.5132 | 0.1394 | 0.0518 | 0.1168 | 0.1171 | 19.0 |
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- | No log | 4.0 | 248 | 2.4980 | 0.1404 | 0.052 | 0.1172 | 0.1176 | 19.0 |
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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: 0.1993
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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 billsum dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 2.3574
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+ - Rouge1: 0.1993
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+ - Rouge2: 0.1009
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+ - Rougel: 0.1702
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+ - Rougelsum: 0.1704
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  - Gen Len: 19.0
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  ## Model description
 
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  The following hyperparameters were used during training:
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  - learning_rate: 2e-05
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+ - train_batch_size: 4
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+ - eval_batch_size: 4
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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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  | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
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+ | No log | 1.0 | 248 | 2.5145 | 0.1394 | 0.0522 | 0.1171 | 0.1172 | 19.0 |
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+ | No log | 2.0 | 496 | 2.4057 | 0.1935 | 0.0951 | 0.1642 | 0.1644 | 19.0 |
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+ | 2.8828 | 3.0 | 744 | 2.3667 | 0.2004 | 0.1024 | 0.1716 | 0.1717 | 19.0 |
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+ | 2.8828 | 4.0 | 992 | 2.3574 | 0.1993 | 0.1009 | 0.1702 | 0.1704 | 19.0 |
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  ### Framework versions
pytorch_model.bin CHANGED
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