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--- |
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language: |
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- en |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- samsum |
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metrics: |
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- rouge |
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pipeline_tag: summarization |
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base_model: google/flan-t5-large |
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model-index: |
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- name: stacked-summaries/flan-t5-large-samsum |
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results: |
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- task: |
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type: summarization |
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name: Summarization |
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dataset: |
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name: samsum |
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type: samsum |
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config: samsum |
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split: test |
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metrics: |
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- type: rouge |
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value: 49.0095 |
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name: ROUGE-1 |
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verified: true |
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verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiNGNhY2RhOTg5ZmU4ZGJiMjI1NjUyYWMwYmM2Mzk4MGEwMjk0NDg2OWYxZDdmM2I4NzBmODNiM2JmNTg1MDJhYSIsInZlcnNpb24iOjF9.YinJDLeqzoU_x5uJbGIgq8ZEs36oC3Pzre_vk2juxngBoXCEw54XWjpvVhKKZXeIgc47otucJFtFwAOPEmt9Bw |
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- type: rouge |
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value: 25.681 |
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name: ROUGE-2 |
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verified: true |
|
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiNDBmNDc4NGMzZGEzYzMzMTFiNzliNjUyYmY0MzNjMmRlMTk4ZTRmZmUxODE0MmY1MjEzOWQ2MGQxMmZmZmQ5MSIsInZlcnNpb24iOjF9.UmRHCmQR5CR-JklBTY1JnjD_Gqz_qMYwdVXhMMvnAynMwAgXkoJZeoxT--usUfdkbqaQ-mLeEvLw7mgNE-NQAw |
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- type: rouge |
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value: 41.4474 |
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name: ROUGE-L |
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verified: true |
|
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiODdiM2IxZTU4NTEyMzlmZDEzYTliZWNjMjM1NTAzMjE5MDY1MDZiZDc2YmE2NzUxOWJhMmQ0NTM5MjRjZjQyMSIsInZlcnNpb24iOjF9.PeJ41sirLWf3HTiJXlSMNoleENJT_X2u4VMkgQTmXMmGkbrONTFbUYwO4qjoQkvyjy8pLA2eQ3Fjm5yAvKrTCQ |
|
- type: rouge |
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value: 45.1556 |
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name: ROUGE-LSUM |
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verified: true |
|
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiNGFiMGNkZDYxZmVhMDFlNDRlNmQ4YWVlMTk3ODI0ZWQ2MmIzNWFkYjkwOWRlNzkyNGVmYmY5ZTczZDAxYTk3NiIsInZlcnNpb24iOjF9.dsicHh5W4ba8t8eBBcSRUm-HLPlMoRc57XixiOHBCk-82De5u8hH8fsRWbMmaLpobdJ7b3xlIaVfTfMMRoLvBw |
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- type: loss |
|
value: 1.2201015949249268 |
|
name: loss |
|
verified: true |
|
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiMzliODE2YzY2MzMyZDQ4YzdjZmFjNTc2NDU3ZjQwNjYwNTdhZjY1NWViM2VhNDc1MjQzNDkxMDI2MTM5ZjFkYiIsInZlcnNpb24iOjF9.2QdP4Zj2oHCo0HCoGgZy6YdqNJaQ0ri0E2kD7lzYbVmyg35wyGutvRUaXVR6O833gTbsCvM86Gp77qNT9CTyDA |
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- type: gen_len |
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value: 17.326 |
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name: gen_len |
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verified: true |
|
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiMWJlNjhjMmUxNWU3MDZlMTUzOWRmM2UwNmU3MjBjODhmMGYxZTUyMmFmMmE0MmU3ZTVkYWY0MDhkMWQ3NTk2MSIsInZlcnNpb24iOjF9.wFaw7DOpESjPu_uW6liHc4XaTwF36ReLLYd-BBFhnZXemE_lGQxmp0O0Vl2DgZz3SSbXonyS4D01G2hYze8qCA |
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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-large-samsum |
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This model is a fine-tuned version of [google/flan-t5-large](https://huggingface.co/google/flan-t5-large) on the samsum dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.1754 |
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- Rouge1: 54.1595 |
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- Rouge2: 29.1081 |
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- Rougel: 45.4989 |
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- Rougelsum: 49.1026 |
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- Gen Len: 28.72 |
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> Note: the stacked version of this model technically does evaluation on a **different** validation set (the stacked one) while this just uses `samsum`. |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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- Intended for comparison(s) to the [stacked version of this model](https://huggingface.co/stacked-summaries/flan-t5-large-stacked-samsum-1024) |
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- 1024 token input max |
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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: 8 |
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- eval_batch_size: 4 |
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- seed: 17868 |
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- distributed_type: multi-GPU |
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- gradient_accumulation_steps: 16 |
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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: cosine |
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- lr_scheduler_warmup_ratio: 0.04 |
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- num_epochs: 5.0 |
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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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| 1.2106 | 0.43 | 50 | 1.1889 | 52.5898 | 26.9967 | 43.6944 | 47.9656 | 24.5167 | |
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| 1.213 | 0.87 | 100 | 1.1760 | 52.4279 | 27.4689 | 43.7873 | 48.0581 | 25.0533 | |
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| 1.0726 | 1.3 | 150 | 1.1731 | 52.8246 | 26.9524 | 43.7429 | 48.0345 | 25.55 | |
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| 1.0784 | 1.74 | 200 | 1.1708 | 53.1291 | 27.9056 | 44.2609 | 48.6883 | 26.03 | |
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| 1.0215 | 2.17 | 250 | 1.1755 | 53.1512 | 27.9475 | 44.1442 | 48.4619 | 27.57 | |
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| 1.0294 | 2.61 | 300 | 1.1711 | 53.4402 | 28.0126 | 44.5454 | 48.6432 | 25.9033 | |
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| 1.0016 | 3.04 | 350 | 1.1718 | 53.9395 | 28.3087 | 45.191 | 49.2773 | 26.6133 | |
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| 0.9576 | 3.48 | 400 | 1.1741 | 53.9004 | 28.3243 | 45.0911 | 48.9182 | 26.33 | |
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| 0.9739 | 3.91 | 450 | 1.1754 | 53.7049 | 28.419 | 44.8946 | 48.8708 | 27.2433 | |
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| 0.9505 | 4.35 | 500 | 1.1781 | 53.7142 | 28.1758 | 44.8324 | 48.9498 | 26.8667 | |
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| 0.9993 | 4.78 | 550 | 1.1784 | 53.87 | 28.2211 | 44.893 | 49.1074 | 27.2167 | |
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