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CommitPredictorT5

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

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@@ -17,7 +17,7 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [Salesforce/codet5-base-multi-sum](https://huggingface.co/Salesforce/codet5-base-multi-sum) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 2.4965
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  - Rouge1: 0.0001
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  - Rouge2: 0.0
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  - Rougel: 0.0001
@@ -48,23 +48,31 @@ 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: 30
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | Bleu |
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- |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|:------:|
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- | 3.2251 | 1.0 | 837 | 2.6716 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0003 |
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- | 2.6363 | 2.0 | 1674 | 2.5424 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0003 |
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- | 2.4269 | 3.0 | 2511 | 2.4765 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0003 |
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- | 2.2842 | 4.0 | 3348 | 2.4356 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0003 |
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- | 2.1366 | 5.0 | 4185 | 2.4353 | 0.0001 | 0.0 | 0.0001 | 0.0001 | 1.0 | 0.0003 |
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- | 2.0199 | 6.0 | 5022 | 2.4261 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0003 |
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- | 1.9309 | 7.0 | 5859 | 2.4334 | 0.0001 | 0.0 | 0.0001 | 0.0001 | 1.0 | 0.0003 |
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- | 1.8353 | 8.0 | 6696 | 2.4361 | 0.0001 | 0.0 | 0.0001 | 0.0001 | 1.0 | 0.0003 |
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- | 1.7459 | 9.0 | 7533 | 2.4576 | 0.0001 | 0.0 | 0.0001 | 0.0001 | 1.0 | 0.0003 |
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- | 1.6658 | 10.0 | 8370 | 2.4634 | 0.0001 | 0.0 | 0.0001 | 0.0001 | 1.0 | 0.0003 |
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- | 1.594 | 11.0 | 9207 | 2.4965 | 0.0001 | 0.0 | 0.0001 | 0.0001 | 1.0 | 0.0003 |
 
 
 
 
 
 
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [Salesforce/codet5-base-multi-sum](https://huggingface.co/Salesforce/codet5-base-multi-sum) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 2.7383
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  - Rouge1: 0.0001
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  - Rouge2: 0.0
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  - Rougel: 0.0001
 
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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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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | Bleu |
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+ |:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|:------:|
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+ | 3.2223 | 1.0 | 837 | 2.6672 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0003 |
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+ | 2.6296 | 2.0 | 1674 | 2.5416 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0003 |
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+ | 2.4155 | 3.0 | 2511 | 2.4725 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0003 |
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+ | 2.2666 | 4.0 | 3348 | 2.4331 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0003 |
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+ | 2.112 | 5.0 | 4185 | 2.4343 | 0.0001 | 0.0 | 0.0001 | 0.0001 | 1.0 | 0.0003 |
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+ | 1.9833 | 6.0 | 5022 | 2.4283 | 0.0001 | 0.0 | 0.0001 | 0.0001 | 1.0 | 0.0003 |
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+ | 1.8833 | 7.0 | 5859 | 2.4360 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0003 |
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+ | 1.7778 | 8.0 | 6696 | 2.4457 | 0.0001 | 0.0 | 0.0001 | 0.0001 | 1.0 | 0.0003 |
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+ | 1.6767 | 9.0 | 7533 | 2.4696 | 0.0001 | 0.0 | 0.0001 | 0.0001 | 1.0 | 0.0003 |
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+ | 1.5805 | 10.0 | 8370 | 2.4829 | 0.0001 | 0.0 | 0.0001 | 0.0001 | 1.0 | 0.0003 |
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+ | 1.4918 | 11.0 | 9207 | 2.5202 | 0.0001 | 0.0 | 0.0001 | 0.0001 | 1.0 | 0.0003 |
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+ | 1.4137 | 12.0 | 10044 | 2.5357 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0003 |
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+ | 1.3351 | 13.0 | 10881 | 2.5621 | 0.0001 | 0.0 | 0.0001 | 0.0001 | 1.0 | 0.0003 |
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+ | 1.2533 | 14.0 | 11718 | 2.5992 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0003 |
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+ | 1.1952 | 15.0 | 12555 | 2.6149 | 0.0001 | 0.0 | 0.0001 | 0.0001 | 1.0 | 0.0003 |
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+ | 1.122 | 16.0 | 13392 | 2.6565 | 0.0001 | 0.0 | 0.0001 | 0.0001 | 1.0 | 0.0003 |
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+ | 1.0543 | 17.0 | 14229 | 2.6823 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0003 |
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+ | 1.0017 | 18.0 | 15066 | 2.7106 | 0.0001 | 0.0 | 0.0001 | 0.0001 | 1.0 | 0.0003 |
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+ | 0.9437 | 19.0 | 15903 | 2.7383 | 0.0001 | 0.0 | 0.0001 | 0.0001 | 1.0 | 0.0003 |
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  ### Framework versions