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Training complete
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README.md
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---
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license: apache-2.0
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library_name: peft
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tags:
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- Summarization
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- generated_from_trainer
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datasets:
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- cnn_dailymail
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metrics:
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- rouge
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base_model: google/flan-t5-base
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model-index:
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- name: flan-t5-base-finetuned-QLoRA-10000
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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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# flan-t5-base-finetuned-QLoRA-10000
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This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) on the cnn_dailymail dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.0625
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- Rouge1: 0.2397
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- Rouge2: 0.1107
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- Rougel: 0.1948
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- Rougelsum: 0.226
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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: 3e-05
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- train_batch_size: 8
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- eval_batch_size: 8
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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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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
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|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|
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| 1.3695 | 1.0 | 1250 | 1.1374 | 0.232 | 0.1046 | 0.1884 | 0.218 |
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| 1.197 | 2.0 | 2500 | 1.0885 | 0.2371 | 0.1093 | 0.1934 | 0.2236 |
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| 1.1489 | 3.0 | 3750 | 1.0765 | 0.2389 | 0.1098 | 0.1939 | 0.2248 |
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| 1.156 | 4.0 | 5000 | 1.0693 | 0.2403 | 0.1107 | 0.195 | 0.226 |
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| 1.1135 | 5.0 | 6250 | 1.0663 | 0.2393 | 0.1102 | 0.1944 | 0.2252 |
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| 1.1607 | 6.0 | 7500 | 1.0648 | 0.24 | 0.1109 | 0.1951 | 0.2259 |
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| 1.1222 | 7.0 | 8750 | 1.0635 | 0.2398 | 0.1106 | 0.1947 | 0.2256 |
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| 1.1619 | 8.0 | 10000 | 1.0629 | 0.2399 | 0.1106 | 0.1949 | 0.2259 |
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| 1.1366 | 9.0 | 11250 | 1.0626 | 0.2397 | 0.1108 | 0.1948 | 0.226 |
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| 1.2062 | 10.0 | 12500 | 1.0625 | 0.2397 | 0.1107 | 0.1948 | 0.226 |
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### Framework versions
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- PEFT 0.8.2
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- Transformers 4.37.0
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- Pytorch 2.1.2
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- Datasets 2.1.0
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- Tokenizers 0.15.1
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