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IndicBART-finetuned-mr-sum
october-sd/IndicBART-finetuned-mr-sum
IndicBART-finetuned-mr-sum is a summarization model from october-sd. 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
- mbart
- Access
- Public
- Created
- Mar 3, 2024
- Updated
- Mar 8, 2024
- SHA
- 5a9ee1fe
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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. -->
IndicBART-finetuned-mr-sum
This model is a fine-tuned version of october-sd/IndicBART-finetuned-mr-sum on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.1235
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.7407 | 1.0 | 1803 | 2.0960 |
| 1.6836 | 2.0 | 3606 | 2.1042 |
| 1.6393 | 3.0 | 5409 | 2.1098 |
| 1.6129 | 4.0 | 7212 | 2.1235 |
Framework versions
- Transformers 4.38.1
- Pytorch 2.1.2
- Datasets 2.15.0
- Tokenizers 0.15.2
- Task
- Summarization
- Library
- transformers
- Type
- mbart
- Created
- Mar 3, 2024
- Updated
- Mar 8, 2024