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bart-base-reddit_tifu-rouge-3-loss-differentiable-10-cnt-supervised-sequential
taiypeo/bart-base-reddit_tifu-rouge-3-loss-differentiable-10-cnt-supervised-sequential
bart-base-reddit_tifu-rouge-3-loss-differentiable-10-cnt-supervised-sequential is a machine learning model from taiypeo. 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 transformers. 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
- transformers
- License
- apache-2.0
- Model type
- bart
- Access
- Public
- Created
- Dec 6, 2025
- Updated
- Dec 6, 2025
- SHA
- 7861e661
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. -->
bart-base-reddit_tifu-rouge-3-loss-differentiable-10-cnt-supervised-sequential
This model is a fine-tuned version of taiypeo/bart-base-reddit_tifu-sentence-paraphrased-10-cnt-supervised-basic on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 3.5611
- Rouge1: 0.1665
- Rouge2: 0.0357
- Rougel: 0.1316
- Rougelsum: 0.1316
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: 1e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Use adamw_torch_fused with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.06
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|---|---|---|---|---|---|---|---|
| 1.2191 | 0.0032 | 2 | 3.5596 | 0.1665 | 0.0359 | 0.1313 | 0.1314 |
| 1.1847 | 0.0064 | 4 | 3.5611 | 0.1665 | 0.0357 | 0.1316 | 0.1316 |
| 1.2488 | 0.0096 | 6 | 3.5639 | 0.166 | 0.0351 | 0.1312 | 0.1312 |
| 1.4996 | 0.0128 | 8 | 3.5681 | 0.1657 | 0.0347 | 0.131 | 0.131 |
| 1.3808 | 0.0160 | 10 | 3.5738 | 0.1654 | 0.0346 | 0.1308 | 0.1308 |
| 1.255 | 0.0192 | 12 | 3.5811 | 0.1656 | 0.0348 | 0.131 | 0.1309 |
| 1.2889 | 0.0224 | 14 | 3.5899 | 0.1656 | 0.0343 | 0.1308 | 0.1309 |
| 1.2076 | 0.0256 | 16 | 3.6007 | 0.1668 | 0.035 | 0.1316 | 0.1315 |
Framework versions
- Transformers 4.57.3
- Pytorch 2.9.1+cu128
- Datasets 3.6.0
- Tokenizers 0.22.1
- Library
- transformers
- Type
- bart
- License
- apache-2.0
- Created
- Dec 6, 2025
- Updated
- Dec 6, 2025