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mBART-TextSimp-LT-BatchSize2-lr1e-4
eglkan1/mBART-TextSimp-LT-BatchSize2-lr1e-4
mBART-TextSimp-LT-BatchSize2-lr1e-4 is a machine learning model from eglkan1. 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 mit.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- transformers
- License
- mit
- Model type
- mbart
- Access
- Public
- Created
- Apr 9, 2024
- Updated
- Apr 11, 2024
- SHA
- d7837eee
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. -->
mBART-TextSimp-LT-BatchSize2-lr1e-4
This model is a fine-tuned version of facebook/mbart-large-50 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0962
- Rouge1: 0.76
- Rouge2: 0.6246
- Rougel: 0.7508
- Sacrebleu: 53.9078
- Gen Len: 32.9976
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: 0.0001
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 8
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Sacrebleu | Gen Len |
|---|---|---|---|---|---|---|---|---|
| 0.0639 | 1.0 | 418 | 0.0779 | 0.7012 | 0.5432 | 0.6904 | 43.0798 | 32.9976 |
| 0.0653 | 2.0 | 836 | 0.0732 | 0.7197 | 0.5593 | 0.7091 | 44.8483 | 32.9976 |
| 0.0327 | 3.0 | 1254 | 0.0726 | 0.7319 | 0.5787 | 0.7206 | 47.842 | 32.9976 |
| 0.0168 | 4.0 | 1672 | 0.0782 | 0.7466 | 0.6031 | 0.7371 | 50.9225 | 32.9976 |
| 0.013 | 5.0 | 2090 | 0.0804 | 0.7507 | 0.6077 | 0.7409 | 51.8293 | 32.9976 |
| 0.0032 | 6.0 | 2508 | 0.0846 | 0.7606 | 0.6237 | 0.7507 | 53.5224 | 32.9976 |
| 0.0012 | 7.0 | 2926 | 0.0911 | 0.7597 | 0.6263 | 0.751 | 54.0182 | 32.9976 |
| 0.0012 | 8.0 | 3344 | 0.0962 | 0.76 | 0.6246 | 0.7508 | 53.9078 | 32.9976 |
Framework versions
- Transformers 4.33.0
- Pytorch 2.1.2+cu121
- Datasets 2.14.4
- Tokenizers 0.13.3
- Library
- transformers
- Type
- mbart
- License
- mit
- Created
- Apr 9, 2024
- Updated
- Apr 11, 2024