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---
base_model: Hasanur525/deed-summarization_version_5
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: deed-summarization_version_10
results: []
---
<!-- 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. -->
# deed-summarization_version_10
This model is a fine-tuned version of [Hasanur525/deed-summarization_version_5](https://huggingface.co./Hasanur525/deed-summarization_version_5) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4150
- Rouge1: 0.3247
- Rouge2: 0.1432
- Rougel: 0.3268
- Rougelsum: 0.3201
- Gen Len: 98.4206
## 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: 2e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 5000
- num_epochs: 20
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 2.6983 | 1.0 | 529 | 1.8154 | 0.0 | 0.0 | 0.0 | 0.0 | 72.9565 |
| 2.3213 | 2.0 | 1058 | 1.5403 | 0.0 | 0.0 | 0.0 | 0.0 | 82.2401 |
| 1.0315 | 3.0 | 1587 | 1.2686 | 0.0 | 0.0 | 0.0 | 0.0 | 88.1635 |
| 1.7308 | 4.0 | 2116 | 1.0681 | 0.0 | 0.0 | 0.0 | 0.0 | 89.7155 |
| 1.1384 | 5.0 | 2645 | 0.9338 | 0.0 | 0.0 | 0.0 | 0.0 | 93.0586 |
| 1.6608 | 6.0 | 3174 | 0.8329 | 0.0199 | 0.0 | 0.0199 | 0.0199 | 95.5454 |
| 1.8287 | 7.0 | 3703 | 0.7506 | 0.0099 | 0.0 | 0.0099 | 0.0099 | 96.9036 |
| 0.4304 | 8.0 | 4232 | 0.6827 | 0.0742 | 0.036 | 0.0692 | 0.069 | 96.8894 |
| 1.1026 | 9.0 | 4761 | 0.6189 | 0.0888 | 0.0516 | 0.0888 | 0.0859 | 97.5312 |
| 0.8345 | 10.0 | 5290 | 0.5662 | 0.0497 | 0.0189 | 0.0443 | 0.0443 | 96.8025 |
| 0.3368 | 11.0 | 5819 | 0.5291 | 0.0394 | 0.0258 | 0.0398 | 0.0394 | 97.9783 |
| 0.2668 | 12.0 | 6348 | 0.5010 | 0.1466 | 0.0379 | 0.1368 | 0.1345 | 97.4386 |
| 0.8294 | 13.0 | 6877 | 0.4787 | 0.1815 | 0.0683 | 0.1744 | 0.167 | 97.8639 |
| 0.4896 | 14.0 | 7406 | 0.4603 | 0.1946 | 0.0732 | 0.1948 | 0.1899 | 97.707 |
| 0.4353 | 15.0 | 7935 | 0.4446 | 0.158 | 0.0664 | 0.1476 | 0.1456 | 97.8837 |
| 1.8165 | 16.0 | 8464 | 0.4314 | 0.3104 | 0.1119 | 0.3005 | 0.2917 | 98.4329 |
| 0.3503 | 17.0 | 8993 | 0.4236 | 0.2872 | 0.1234 | 0.2785 | 0.2681 | 98.2259 |
| 0.5756 | 18.0 | 9522 | 0.4199 | 0.339 | 0.1242 | 0.3348 | 0.3252 | 98.31 |
| 0.7974 | 19.0 | 10051 | 0.4176 | 0.3437 | 0.1568 | 0.3477 | 0.338 | 98.3932 |
| 0.224 | 20.0 | 10580 | 0.4150 | 0.3247 | 0.1432 | 0.3268 | 0.3201 | 98.4206 |
### Framework versions
- Transformers 4.37.2
- Pytorch 2.1.0.dev20230811+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2
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