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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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datasets: |
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- samsum |
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metrics: |
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- rouge |
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model-index: |
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- name: switch-base-8-finetuned-samsum |
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results: |
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- task: |
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name: Sequence-to-sequence Language Modeling |
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type: text2text-generation |
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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: train |
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args: samsum |
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metrics: |
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- name: Rouge1 |
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type: rouge |
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value: 46.1297 |
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widget: |
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- text: |- |
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Sid: Wanna catch a movie? |
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Annie: sure what do you have in mind? |
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Sid; the Aquaman? :D |
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Annie: haha isn't it a bit childish |
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Sid: noooooo I mean yes but it's the highest grossing movie this week |
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Annie: seriously? |
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Sid: yeah? |
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Annie: okay let's see what the fuss is all about |
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- text: |- |
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Manu: What are you doing? |
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Julien: CTO tasks |
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Manu: Sounds boring... |
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Julien: yes you know :S |
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Manu: why don't you come home to see my pets? |
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Julien: sounds like a plan!!! |
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Manu: so, are you coming? |
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Julien: it seems so... ;) |
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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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# Switch Transformer (base-8) fine-tuned on samsum dataset for conversation summarization |
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This model is a fine-tuned version of [google/switch-base-8](https://huggingface.co/google/switch-base-8) on the samsum dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.4614 |
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- Rouge1: 46.1297 |
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- Rouge2: 22.9128 |
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- Rougel: 39.153 |
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- Rougelsum: 42.8502 |
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- Gen Len: 16.9719 |
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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: 5e-05 |
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- train_batch_size: 4 |
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- eval_batch_size: 4 |
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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: 6 |
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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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| 1.8874 | 1.0 | 3683 | 1.5210 | 45.7651 | 22.9379 | 38.8554 | 42.6269 | 17.2482 | |
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| 1.6301 | 2.0 | 7366 | 1.4628 | 47.2719 | 24.8976 | 40.3913 | 43.9285 | 16.8362 | |
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| 1.4326 | 3.0 | 11049 | 1.4402 | 47.8275 | 25.2262 | 40.617 | 44.2948 | 16.9523 | |
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| 1.2992 | 4.0 | 14732 | 1.4489 | 48.393 | 25.3888 | 40.9534 | 44.797 | 17.1504 | |
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| 1.2259 | 5.0 | 18415 | 1.4495 | 49.2186 | 26.312 | 41.721 | 45.5087 | 17.1956 | |
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| 1.1477 | 6.0 | 22098 | 1.4610 | 49.0018 | 26.3474 | 41.5217 | 45.4081 | 17.0782 | |
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### Framework versions |
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- Transformers 4.25.1 |
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- Pytorch 1.13.0+cu116 |
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- Datasets 2.8.0 |
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- Tokenizers 0.13.2 |
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