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---
base_model: eslamxm/MBart-finetuned-ur-xlsum
tags:
- generated_from_trainer
model-index:
- name: 1m-model
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. -->
# 1m-model
This model is a fine-tuned version of [eslamxm/MBart-finetuned-ur-xlsum](https://huggingface.co/eslamxm/MBart-finetuned-ur-xlsum) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5999
## 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: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 1
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.862 | 0.1 | 500 | 0.7994 |
| 0.7785 | 0.2 | 1000 | 0.7464 |
| 0.7568 | 0.3 | 1500 | 0.7119 |
| 0.6927 | 0.4 | 2000 | 0.6837 |
| 0.7486 | 0.49 | 2500 | 0.6636 |
| 0.7208 | 0.59 | 3000 | 0.6463 |
| 0.6784 | 0.69 | 3500 | 0.6297 |
| 0.6286 | 0.79 | 4000 | 0.6166 |
| 0.6339 | 0.89 | 4500 | 0.6063 |
| 0.6738 | 0.99 | 5000 | 0.5999 |
### Framework versions
- Transformers 4.36.2
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.15.0
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