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GlycerinLOL
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LLM_Teached_Pegasus_50k

Text2Text Generation
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pegasus
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  1. README.md +18 -16
  2. model.safetensors +1 -1
  3. runs/Mar02_13-27-43_oi5vv8ctr1709312124223-tkfr5/events.out.tfevents.1709357276.oi5vv8ctr1709312124223-tkfr5.28786.0 +2 -2
README.md CHANGED
@@ -19,15 +19,15 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [google/pegasus-xsum](https://huggingface.co/google/pegasus-xsum) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.7193
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- - Rouge1: 0.4541
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- - Rouge2: 0.2071
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- - Rougel: 0.3708
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- - Rougelsum: 0.3708
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- - Gen Len: 26.4531
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- - Precision: 0.9082
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- - Recall: 0.9061
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- - F1: 0.907
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  ## Model description
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@@ -54,17 +54,19 @@ The following hyperparameters were used during training:
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  - total_train_batch_size: 128
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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 | Precision | Recall | F1 |
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- |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|:---------:|:------:|:------:|
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- | No log | 1.0 | 390 | 1.8258 | 0.4338 | 0.1906 | 0.3496 | 0.3498 | 26.2967 | 0.9049 | 0.9023 | 0.9034 |
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- | 2.1621 | 2.0 | 781 | 1.7537 | 0.4449 | 0.2005 | 0.3633 | 0.3633 | 26.2727 | 0.9068 | 0.9044 | 0.9054 |
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- | 1.8794 | 3.0 | 1172 | 1.7268 | 0.4518 | 0.2061 | 0.3696 | 0.3695 | 26.4345 | 0.9078 | 0.9058 | 0.9066 |
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- | 1.8271 | 3.99 | 1560 | 1.7193 | 0.4541 | 0.2071 | 0.3708 | 0.3708 | 26.4531 | 0.9082 | 0.9061 | 0.907 |
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [google/pegasus-xsum](https://huggingface.co/google/pegasus-xsum) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.6991
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+ - Rouge1: 0.4572
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+ - Rouge2: 0.2103
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+ - Rougel: 0.3743
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+ - Rougelsum: 0.3742
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+ - Gen Len: 26.3378
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+ - Precision: 0.909
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+ - Recall: 0.9067
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+ - F1: 0.9076
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  ## Model description
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  - total_train_batch_size: 128
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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: 6
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  - mixed_precision_training: Native AMP
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  ### Training results
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+ | Training Loss | Epoch | Step | F1 | Gen Len | Validation Loss | Precision | Recall | Rouge1 | Rouge2 | Rougel | Rougelsum |
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+ |:-------------:|:-----:|:----:|:------:|:-------:|:---------------:|:---------:|:------:|:------:|:------:|:------:|:---------:|
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+ | No log | 1.0 | 390 | 0.9034 | 26.2967 | 1.8258 | 0.9049 | 0.9023 | 0.4338 | 0.1906 | 0.3496 | 0.3498 |
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+ | 2.1621 | 2.0 | 781 | 0.9054 | 26.2727 | 1.7537 | 0.9068 | 0.9044 | 0.4449 | 0.2005 | 0.3633 | 0.3633 |
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+ | 1.8794 | 3.0 | 1172 | 0.9066 | 26.4345 | 1.7268 | 0.9078 | 0.9058 | 0.4518 | 0.2061 | 0.3696 | 0.3695 |
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+ | 1.8271 | 4.0 | 1560 | 1.7157 | 0.4539 | 0.2075 | 0.3716 | 0.3714 | 26.3971| 0.9082 | 0.906 | 0.9069 |
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+ | 1.8271 | 5.0 | 1951 | 1.7033 | 0.4561 | 0.2098 | 0.3735 | 0.3734 | 26.3015| 0.9087 | 0.9065 | 0.9074 |
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+ | 1.8067 | 5.99 | 2340 | 1.6991 | 0.4572 | 0.2103 | 0.3743 | 0.3742 | 26.3378| 0.909 | 0.9067 | 0.9076 |
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  ### Framework versions
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