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--- |
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tags: |
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- generated_from_trainer |
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- summarization |
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- book summary |
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metrics: |
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- rouge |
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dataset: |
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- kmfoda/booksum |
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model-index: |
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- name: long-t5-tglobal-large-booksum-WIP |
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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: kmfoda/booksum |
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type: kmfoda/booksum |
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config: kmfoda--booksum |
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split: test |
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metrics: |
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- type: rouge |
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value: 25.6136 |
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name: ROUGE-1 |
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verified: true |
|
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiY2E3ZWI5NjRiZGE3YTQ2YTg5MGNmNzI5NTdjN2U3OTNiNzhmMjBhMDVkZjcwZjg0MTEyMTM3MzQyZmI1NzNjYSIsInZlcnNpb24iOjF9.REYAFwePFucxAn1Twsh9BSov9KPsCML9nTjL9oIIWa3Hp8DwJ_syPmfNsYxGe2vvNVq5rzBKF9gsJW80pbo-Aw |
|
- type: rouge |
|
value: 2.8652 |
|
name: ROUGE-2 |
|
verified: true |
|
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiMzk5Mjg0ZmRjYzg1NjM4MGMwOWYyOTM0ZDU2OTM2ZGJlYmM0OTVjNTI2NzcyMzU0MGI0M2I0ZmE0ZmY2NmRlNSIsInZlcnNpb24iOjF9.MzKSIqRjIV6V5YMYlvbRt2ca_CR5WFZ8DqOrUvDbiSyh7qbdU6F2LdDjB6eL-wzIR_DMF10sTtoF7H7wXs2GDw |
|
- type: rouge |
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value: 12.4913 |
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name: ROUGE-L |
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verified: true |
|
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiZDMzMDZhYzg2N2Q0YTZiYWUzOGI2MTRjMmRlNGIzY2I0ZDU3YzQ1MWVkZDlkOTQzNDlhNjk1MWM2OWUwNDczYSIsInZlcnNpb24iOjF9.TysgYlvfe-4GJWDSFg8KQ97Bsu-kDX3VDamS6bi9q_60V3mBzIOz0M0slySuHXu5S4MJ8a0OCPWvskP0T4ZmCQ |
|
- type: rouge |
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value: 23.1102 |
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name: ROUGE-LSUM |
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verified: true |
|
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiMzY3NmI2MDJkZTQ2MzMwMDg2NWZmM2Q5NjNmZTRkMTJiODViODZmODYyNTgwMzBkYzBmZDRmMWNjYjg5NjBkYSIsInZlcnNpb24iOjF9.XNvINLow-1mfiDbm_YcAM_l4c-gEV_V5oLKzBWh7Hdmi9gHP_Z86fqQn9Kj2nhOPFWcUOFUBIzx4Z0rjs162BA |
|
- type: loss |
|
value: 5.004334926605225 |
|
name: loss |
|
verified: true |
|
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiODNjMzI5N2IwNDExOWQzMWYxMzE4YzkxYWYxZmRkNTA2NWQ1MmYzOTFjODJhNGUzODQxYmNkODBlZDA0MGNmZCIsInZlcnNpb24iOjF9.xGNlloXeHra0K5DTKXbsrrkyuAvFXZwjzkxOyjtpw2jWs0KPw4nQ1MKkJiX6juXtleJrvS2u1FQcwCbygUmLDQ |
|
- type: gen_len |
|
value: 89.4354 |
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name: gen_len |
|
verified: true |
|
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiYjBlODBiMmEwN2UzYzE5NTE3ODBkNDVmMTgxMzhlYmVmZjgxMzJjYTBlYjBhMDgzNzhhMWQ0Mzc2MjdjN2E0ZiIsInZlcnNpb24iOjF9.Z9kytQDiNK-TCaHz-0YZeH8FCrW5D0SA-ji7Q86wqdhBC9jTDmJGnBll6mGFcHipERrRKZb12hYStKJanb3iBA |
|
--- |
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# tglobal-large-booksum-WIP |
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|
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> this is a WIP checkpoint that has been fine-tuned from the vanilla (original) for 10ish epochs. It is **not ready to be used for inference** |
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This model is a fine-tuned version of [google/long-t5-tglobal-large](https://huggingface.co/google/long-t5-tglobal-large) on the `kmfoda/booksum` dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 4.9519 |
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- Rouge1: 21.8058 |
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- Rouge2: 2.9343 |
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- Rougel: 10.3717 |
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- Rougelsum: 20.1537 |
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- Gen Len: 106.055 |
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|
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## Model description |
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Testing fine-tuning only on booksum with 16384/1024 the whole time (vs. previous large WIP checkpoint I made that started from a partially-trained `pubmed` checkpoint) |
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|
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## Intended uses & limitations |
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this is a WIP checkpoint that has been fine-tuned from the vanilla (original) for 10ish epochs. It is **not ready to be used for inference** |
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|
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## Training and evaluation data |
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This is **only** fine-tuned on booksum (vs. previous large WIP checkpoint I made that started from a partially-trained `pubmed` checkpoint) |
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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: 0.0004 |
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- train_batch_size: 1 |
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- eval_batch_size: 1 |
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- seed: 31060 |
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- distributed_type: multi-GPU |
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- num_devices: 4 |
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- gradient_accumulation_steps: 32 |
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- total_train_batch_size: 128 |
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- total_eval_batch_size: 4 |
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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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- num_epochs: 3.0 |
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### Training results |
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| Training Loss | Epoch | Step | Gen Len | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | |
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|:-------------:|:-----:|:----:|:-------:|:---------------:|:-------:|:------:|:-------:|:---------:| |
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| 5.0389 | 0.99 | 37 | 219.03 | 5.1884 | 29.995 | 4.4045 | 12.8837 | 27.557 | |
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| 4.8986 | 1.0 | 75 | 5.1286 | 26.921 | 3.7193 | 11.3605| 25.3492 | 276.005 | |
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| 4.5928 | 2.0 | 150 | 4.9900 | 26.6667 | 3.7342 | 11.8223| 24.7087 | 178.775 | |
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| 4.6159 | 3.0 | 225 | 4.9519 | 21.8058 | 2.9343 | 10.3717| 20.1537 | 106.055 | |
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#### eval in bf16 |
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``` |
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***** eval metrics ***** |
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epoch = 3.0 |
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eval_gen_len = 103.075 |
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eval_loss = 4.9501 |
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eval_rouge1 = 21.6345 |
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eval_rouge2 = 2.877 |
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eval_rougeL = 10.386 |
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eval_rougeLsum = 20.0148 |
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eval_runtime = 0:06:02.75 |
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eval_samples = 200 |
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eval_samples_per_second = 0.551 |
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eval_steps_per_second = 0.138 |
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[INFO|trainer.py:2724] 2022-11-27 01:00: |
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``` |
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### Framework versions |
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- Transformers 4.25.0.dev0 |
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- Pytorch 1.13.0+cu117 |
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- Datasets 2.6.1 |
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- Tokenizers 0.13.1 |
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