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satire-sft-bart_training_full_weighted
narwhalsilent/satire-sft-bart_training_full_weighted
satire-sft-bart_training_full_weighted is a machine learning model from narwhalsilent. 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
- Apr 7, 2026
- Updated
- Apr 7, 2026
- SHA
- d1da2a2b
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. -->
satire-sft-bart_training_full_weighted
This model is a fine-tuned version of facebook/bart-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.3416
- Rouge1: 0.4185
- Rouge2: 0.2063
- Rougel: 0.3825
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: 3e-05
- train_batch_size: 16
- eval_batch_size: 64
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- total_train_batch_size: 32
- total_eval_batch_size: 128
- optimizer: Use OptimizerNames.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_steps: 354
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel |
|---|---|---|---|---|---|---|
| 2.8584 | 1.0 | 710 | 2.5005 | 0.4181 | 0.2029 | 0.3831 |
| 2.6048 | 2.0 | 1420 | 2.3954 | 0.419 | 0.206 | 0.3832 |
| 2.3535 | 3.0 | 2130 | 2.3582 | 0.4208 | 0.2095 | 0.3848 |
| 2.2193 | 4.0 | 2840 | 2.3474 | 0.4225 | 0.2091 | 0.3861 |
| 2.1258 | 5.0 | 3550 | 2.3416 | 0.4185 | 0.2063 | 0.3825 |
Framework versions
- Transformers 5.0.0
- Pytorch 2.10.0+cu128
- Datasets 4.8.3
- Tokenizers 0.22.2
- Library
- transformers
- Type
- bart
- License
- apache-2.0
- Created
- Apr 7, 2026
- Updated
- Apr 7, 2026