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xlmroberta-finetuned-fa
eslamxm/xlmroberta-finetuned-fa
xlmroberta-finetuned-fa is a summarization model from eslamxm. Use it when you need a shorter version of a longer text. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Summarization
- Library
- transformers
- Model type
- encoder-decoder
- Access
- Public
- Created
- Jun 14, 2022
- Updated
- Jun 15, 2022
- SHA
- c1f6097c
Try a prompt
Datasets
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. -->
xlmroberta-finetuned-fa
This model is a fine-tuned version of on the pn_summary dataset. It achieves the following results on the evaluation set:
- Loss: 8.2286
- Rouge-1: 4.99
- Rouge-2: 0.0
- Rouge-l: 4.99
- Gen Len: 20.0
- Bertscore: 51.89
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: 0.0005
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 250
- num_epochs: 5
- label_smoothing_factor: 0.1
Training results
Framework versions
- Transformers 4.19.4
- Pytorch 1.11.0+cu113
- Datasets 2.3.0
- Tokenizers 0.12.1
- Task
- Summarization
- Library
- transformers
- Type
- encoder-decoder
- Created
- Jun 14, 2022
- Updated
- Jun 15, 2022