---
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