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LongT5-XLarge-NSPCC
scott156/LongT5-XLarge-NSPCC
LongT5-XLarge-NSPCC is a machine learning model from scott156. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for peft. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- peft
- License
- apache-2.0
- Access
- Public
- Created
- May 6, 2024
- Updated
- May 6, 2024
- SHA
- 3f7d081a
Base models
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
LongT5-XLarge-NSPCC
This model is a fine-tuned version of google/long-t5-tglobal-xl on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6843
- Rouge1: 0.5138
- Rouge2: 0.2297
- Rougel: 0.2999
- Rougelsum: 0.2995
- Gen Len: 337.6809
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0003
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 4
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| 3.6911 | 0.9960 | 188 | 0.7292 | 0.4665 | 0.1826 | 0.2611 | 0.2611 | 360.7021 |
| 0.8701 | 1.9974 | 377 | 0.6967 | 0.4886 | 0.2073 | 0.2805 | 0.2799 | 365.3298 |
| 0.7849 | 2.9987 | 566 | 0.6808 | 0.5116 | 0.2302 | 0.2995 | 0.2997 | 332.3191 |
| 0.7769 | 3.9841 | 752 | 0.6843 | 0.5138 | 0.2297 | 0.2999 | 0.2995 | 337.6809 |
Framework versions
- PEFT 0.10.0
- Transformers 4.40.1
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1
- Library
- peft
- License
- apache-2.0
- Created
- May 6, 2024
- Updated
- May 6, 2024