Summarization models for Nepali Language
Collection
This collection contains all the models that were created during my project for Nepali Language summarization task
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6 items
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Updated
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Configuration Parsing
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In adapter_config.json: "peft.task_type" must be a string
mt5-base_Nepali_News_Summarization_QLoRA_4bit
This model is a fine-tuned version of google/mt5-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: nan
- Rouge-1 R: 0.0
- Rouge-1 P: 0.0
- Rouge-1 F: 0.0
- Rouge-2 R: 0.0
- Rouge-2 P: 0.0
- Rouge-2 F: 0.0
- Rouge-l R: 0.0
- Rouge-l P: 0.0
- Rouge-l F: 0.0
- Gen Len: 0.0
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: 5
- eval_batch_size: 5
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge-1 R | Rouge-1 P | Rouge-1 F | Rouge-2 R | Rouge-2 P | Rouge-2 F | Rouge-l R | Rouge-l P | Rouge-l F | Gen Len |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.0 | 1.0 | 10191 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 0.0 | 2.0 | 20382 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 0.0 | 3.0 | 30573 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
Framework versions
- PEFT 0.12.0
- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.19.2
- Tokenizers 0.19.1
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Model tree for caspro/mt5-base_Nepali_News_Summarization_QLoRA_4bit
Base model
google/mt5-base