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README.md
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---
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license: apache-2.0
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tags:
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- generated_from_trainer
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metrics:
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- rouge
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model-index:
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- name: mymodel_v2_4
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results: []
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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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should probably proofread and complete it, then remove this comment. -->
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# mymodel_v2_4
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This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co/facebook/bart-base) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 2.1383
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- Rouge1: 0.5107
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- Rouge2: 0.1818
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- Rougel: 0.4557
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- Rougelsum: 0.4753
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- Gen Len: 19.4327
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 0.0001
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- train_batch_size: 10
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- eval_batch_size: 10
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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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| No log | 1.0 | 111 | 1.6651 | 1.0836 | 0.9742 | 1.076 | 1.0681 | 19.4 |
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| No log | 2.0 | 222 | 1.6632 | 0.5545 | 0.3924 | 0.5312 | 0.5302 | 19.5855 |
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| No log | 3.0 | 333 | 1.7607 | 0.7463 | 0.5905 | 0.7663 | 0.7512 | 19.6982 |
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| No log | 4.0 | 444 | 1.8583 | 0.8352 | 0.7153 | 0.8546 | 0.8534 | 19.7018 |
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| 1.4574 | 5.0 | 555 | 1.9357 | 0.659 | 0.6196 | 0.6745 | 0.6962 | 19.3273 |
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| 1.4574 | 6.0 | 666 | 2.0241 | 0.4785 | 0.4545 | 0.4878 | 0.4997 | 19.6036 |
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| 1.4574 | 7.0 | 777 | 2.0663 | 0.2327 | 0.1818 | 0.2741 | 0.2741 | 19.2327 |
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| 1.4574 | 8.0 | 888 | 2.0969 | 0.3755 | 0.2916 | 0.3915 | 0.3956 | 19.4545 |
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| 1.4574 | 9.0 | 999 | 2.1291 | 0.7743 | 0.5592 | 0.7473 | 0.7881 | 19.3964 |
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| 0.3529 | 10.0 | 1110 | 2.1383 | 0.5107 | 0.1818 | 0.4557 | 0.4753 | 19.4327 |
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### Framework versions
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- Transformers 4.28.1
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- Pytorch 2.0.0
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- Datasets 2.1.0
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- Tokenizers 0.13.3
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