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dewifaj
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summarizer_samsum_model

Text2Text Generation
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Safetensors
t5
Generated from Trainer
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text-generation-inference
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End of training

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  1. README.md +17 -11
  2. model.safetensors +1 -1
  3. runs/Mar17_03-17-30_f568924cd75f/events.out.tfevents.1710645451.f568924cd75f.18253.1 +2 -2
README.md CHANGED
@@ -17,12 +17,12 @@ 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 an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.4249
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- - Rouge1: 0.3873
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- - Rouge2: 0.1614
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- - Rougel: 0.3216
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- - Rougelsum: 0.3216
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- - Gen Len: 16.1371
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  ## Model description
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@@ -47,17 +47,23 @@ 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: 4
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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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- | 1.9208 | 1.0 | 737 | 0.4468 | 0.3549 | 0.1408 | 0.2962 | 0.2962 | 15.1235 |
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- | 0.5031 | 2.0 | 1474 | 0.4318 | 0.3769 | 0.1527 | 0.3129 | 0.3129 | 15.9878 |
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- | 0.4758 | 3.0 | 2211 | 0.4272 | 0.3849 | 0.1591 | 0.3197 | 0.3197 | 16.0886 |
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- | 0.4722 | 4.0 | 2948 | 0.4249 | 0.3873 | 0.1614 | 0.3216 | 0.3216 | 16.1371 |
 
 
 
 
 
 
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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: 0.3992
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+ - Rouge1: 0.4144
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+ - Rouge2: 0.1805
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+ - Rougel: 0.3419
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+ - Rougelsum: 0.3418
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+ - Gen Len: 16.6732
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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: 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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+ | 0.4595 | 1.0 | 737 | 0.4170 | 0.3923 | 0.163 | 0.3243 | 0.3242 | 16.1826 |
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+ | 0.4474 | 2.0 | 1474 | 0.4113 | 0.3991 | 0.1685 | 0.3304 | 0.3303 | 16.5925 |
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+ | 0.4416 | 3.0 | 2211 | 0.4092 | 0.4021 | 0.1722 | 0.3337 | 0.3339 | 16.6023 |
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+ | 0.4388 | 4.0 | 2948 | 0.4048 | 0.4062 | 0.1737 | 0.3361 | 0.3361 | 16.5731 |
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+ | 0.4331 | 5.0 | 3685 | 0.4030 | 0.4093 | 0.1758 | 0.3379 | 0.338 | 16.696 |
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+ | 0.4243 | 6.0 | 4422 | 0.4010 | 0.4111 | 0.1778 | 0.3396 | 0.3396 | 16.5728 |
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+ | 0.4234 | 7.0 | 5159 | 0.4000 | 0.4129 | 0.1789 | 0.3406 | 0.3405 | 16.7139 |
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+ | 0.425 | 8.0 | 5896 | 0.3996 | 0.4125 | 0.1797 | 0.3407 | 0.3407 | 16.7089 |
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+ | 0.4247 | 9.0 | 6633 | 0.3993 | 0.4147 | 0.181 | 0.3421 | 0.3422 | 16.6943 |
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+ | 0.4176 | 10.0 | 7370 | 0.3992 | 0.4144 | 0.1805 | 0.3419 | 0.3418 | 16.6732 |
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  ### Framework versions
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