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---
base_model: csebuetnlp/mT5_multilingual_XLSum
tags:
- generated_from_trainer
model-index:
- name: HappyNews_1_loadbest
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. -->
# HappyNews_1_loadbest
This model is a fine-tuned version of [csebuetnlp/mT5_multilingual_XLSum](https://huggingface.co./csebuetnlp/mT5_multilingual_XLSum) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 3.1967
## 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: 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: 1000
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 4.1092 | 0.29 | 100 | 4.0260 |
| 4.3545 | 0.58 | 200 | 3.6022 |
| 3.818 | 0.87 | 300 | 3.3815 |
| 3.2577 | 1.16 | 400 | 3.2590 |
| 3.1005 | 1.45 | 500 | 3.1290 |
| 3.0309 | 1.73 | 600 | 3.0690 |
| 3.0128 | 2.02 | 700 | 3.0172 |
| 2.4054 | 2.31 | 800 | 3.0086 |
| 2.7848 | 2.6 | 900 | 3.0103 |
| 2.4307 | 2.89 | 1000 | 2.9606 |
| 2.3408 | 3.18 | 1100 | 2.9490 |
| 2.4232 | 3.47 | 1200 | 2.9333 |
| 2.5301 | 3.76 | 1300 | 2.9138 |
| 1.9984 | 4.05 | 1400 | 2.9422 |
| 2.1215 | 4.34 | 1500 | 2.9620 |
| 1.859 | 4.62 | 1600 | 2.9550 |
| 1.8986 | 4.91 | 1700 | 2.9654 |
| 1.847 | 5.2 | 1800 | 3.0660 |
| 1.7843 | 5.49 | 1900 | 3.0169 |
| 1.9724 | 5.78 | 2000 | 3.0131 |
| 1.6603 | 6.07 | 2100 | 3.0816 |
| 1.4024 | 6.36 | 2200 | 3.0947 |
| 1.2758 | 6.65 | 2300 | 3.0688 |
| 1.7435 | 6.94 | 2400 | 3.0203 |
| 1.2973 | 7.23 | 2500 | 3.1221 |
| 1.282 | 7.51 | 2600 | 3.1566 |
| 1.4837 | 7.8 | 2700 | 3.1047 |
| 1.6313 | 8.09 | 2800 | 3.1343 |
| 1.4611 | 8.38 | 2900 | 3.1634 |
| 1.0115 | 8.67 | 3000 | 3.1751 |
| 1.4337 | 8.96 | 3100 | 3.1701 |
| 1.1845 | 9.25 | 3200 | 3.1881 |
| 1.2019 | 9.54 | 3300 | 3.1998 |
| 1.1448 | 9.83 | 3400 | 3.1967 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1
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