md_mt5_0109_v7 / README.md
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---
license: apache-2.0
base_model: Buseak/md_mt5_0109_v6
tags:
- generated_from_trainer
metrics:
- bleu
model-index:
- name: md_mt5_0109_v7
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. -->
# md_mt5_0109_v7
This model is a fine-tuned version of [Buseak/md_mt5_0109_v6](https://huggingface.co/Buseak/md_mt5_0109_v6) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0600
- Bleu: 0.6466
- Gen Len: 18.9431
## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15
### Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:-------:|
| 0.1769 | 1.0 | 975 | 0.0816 | 0.6214 | 18.9392 |
| 0.1686 | 2.0 | 1950 | 0.0776 | 0.6253 | 18.9385 |
| 0.1668 | 3.0 | 2925 | 0.0742 | 0.6317 | 18.941 |
| 0.1618 | 4.0 | 3900 | 0.0711 | 0.6321 | 18.9413 |
| 0.1596 | 5.0 | 4875 | 0.0692 | 0.6355 | 18.9408 |
| 0.1575 | 6.0 | 5850 | 0.0670 | 0.6403 | 18.9426 |
| 0.1486 | 7.0 | 6825 | 0.0661 | 0.6419 | 18.9423 |
| 0.1504 | 8.0 | 7800 | 0.0636 | 0.6447 | 18.9428 |
| 0.1476 | 9.0 | 8775 | 0.0632 | 0.6443 | 18.9423 |
| 0.1432 | 10.0 | 9750 | 0.0623 | 0.6447 | 18.9428 |
| 0.1438 | 11.0 | 10725 | 0.0610 | 0.6464 | 18.9423 |
| 0.1411 | 12.0 | 11700 | 0.0607 | 0.6453 | 18.9431 |
| 0.1425 | 13.0 | 12675 | 0.0604 | 0.6475 | 18.9431 |
| 0.1437 | 14.0 | 13650 | 0.0602 | 0.6466 | 18.9431 |
| 0.1416 | 15.0 | 14625 | 0.0600 | 0.6466 | 18.9431 |
### Framework versions
- Transformers 4.38.1
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2