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---
license: apache-2.0
base_model: bakrianoo/t5-arabic-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: results_ara_t5_v2
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. -->
# results_ara_t5_v2
This model is a fine-tuned version of [bakrianoo/t5-arabic-base](https://huggingface.co/bakrianoo/t5-arabic-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Gen Len: 19.0
- Loss: 0.0001
- Rouge1: 0.0875
- Rouge2: 0.0046
- Rougel: 0.0871
- Rougelsum: 0.0873
## 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: 5e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Gen Len | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:-----:|:-----:|:-------:|:---------------:|:------:|:------:|:------:|:---------:|
| 5.4255 | 0.43 | 500 | 18.8641 | 0.0292 | 0.0123 | 0.0028 | 0.0122 | 0.0122 |
| 0.0975 | 0.86 | 1000 | 18.7006 | 0.0101 | 0.0146 | 0.0038 | 0.0146 | 0.0146 |
| 0.0321 | 1.29 | 1500 | 18.5583 | 0.0077 | 0.078 | 0.0046 | 0.0779 | 0.078 |
| 0.0237 | 1.71 | 2000 | 18.7994 | 0.0075 | 0.0806 | 0.0066 | 0.0809 | 0.0805 |
| 0.0182 | 2.14 | 2500 | 19.0 | 0.0072 | 0.0761 | 0.0023 | 0.0759 | 0.076 |
| 0.0148 | 2.57 | 3000 | 18.8528 | 0.0069 | 0.0952 | 0.0061 | 0.0957 | 0.0951 |
| 0.0156 | 3.0 | 3500 | 19.0 | 0.0064 | 0.0773 | 0.0036 | 0.0772 | 0.0772 |
| 0.0126 | 3.43 | 4000 | 18.5583 | 0.0060 | 0.0859 | 0.0038 | 0.0862 | 0.0862 |
| 0.0165 | 3.86 | 4500 | 18.8528 | 0.0056 | 0.0832 | 0.0075 | 0.0835 | 0.0833 |
| 0.0101 | 4.28 | 5000 | 19.0 | 0.0047 | 0.0846 | 0.0052 | 0.0853 | 0.0848 |
| 0.0089 | 4.71 | 5500 | 19.0 | 0.0022 | 0.0874 | 0.0046 | 0.0871 | 0.0873 |
| 0.0063 | 5.14 | 6000 | 19.0 | 0.0009 | 0.0875 | 0.0046 | 0.0871 | 0.0873 |
| 0.0051 | 5.57 | 6500 | 19.0 | 0.0003 | 0.0875 | 0.0046 | 0.0871 | 0.0873 |
| 0.0042 | 6.0 | 7000 | 19.0 | 0.0002 | 0.0875 | 0.0046 | 0.0871 | 0.0873 |
| 0.0037 | 6.43 | 7500 | 19.0 | 0.0002 | 0.0875 | 0.0046 | 0.0871 | 0.0873 |
| 0.0035 | 6.86 | 8000 | 19.0 | 0.0001 | 0.0875 | 0.0046 | 0.0871 | 0.0873 |
| 0.003 | 7.28 | 8500 | 19.0 | 0.0001 | 0.0875 | 0.0046 | 0.0871 | 0.0873 |
| 0.0027 | 7.71 | 9000 | 19.0 | 0.0001 | 0.0875 | 0.0046 | 0.0871 | 0.0873 |
| 0.0024 | 8.14 | 9500 | 19.0 | 0.0001 | 0.0875 | 0.0046 | 0.0871 | 0.0873 |
| 0.0023 | 8.57 | 10000 | 19.0 | 0.0001 | 0.0875 | 0.0046 | 0.0871 | 0.0873 |
| 0.0022 | 9.0 | 10500 | 19.0 | 0.0001 | 0.0875 | 0.0046 | 0.0871 | 0.0873 |
| 0.002 | 9.43 | 11000 | 19.0 | 0.0001 | 0.0875 | 0.0046 | 0.0871 | 0.0873 |
| 0.0019 | 9.85 | 11500 | 19.0 | 0.0001 | 0.0875 | 0.0046 | 0.0871 | 0.0873 |
### Framework versions
- Transformers 4.40.0.dev0
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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