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language:
- vie
- lao
license: apache-2.0
base_model: google/mt5-xl
tags:
- generated_from_trainer
metrics:
- bleu
model-index:
- name: mt5-full-v6.1
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. -->
# mt5-full-v6.1
This model is a fine-tuned version of [google/mt5-xl](https://huggingface.co/google/mt5-xl) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8711
- Bleu: 19.5743
- Gen Len: 41.77
## 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-06
- train_batch_size: 2
- eval_batch_size: 2
- seed: 3435
- gradient_accumulation_steps: 2
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Bleu | Gen Len | Validation Loss |
|:-------------:|:-----:|:------:|:------:|:-------:|:---------------:|
| 1.5671 | 0.14 | 5000 | 6.5196 | 18.9699 | 1.1691 |
| 1.2277 | 0.28 | 10000 | 7.082 | 18.9724 | 1.0592 |
| 1.1316 | 0.42 | 15000 | 7.3283 | 18.9825 | 1.0112 |
| 1.0833 | 0.56 | 20000 | 7.4462 | 18.977 | 0.9728 |
| 1.0339 | 0.7 | 25000 | 8.0126 | 18.982 | 0.9546 |
| 1.025 | 0.83 | 30000 | 7.7648 | 18.9805 | 0.9337 |
| 0.9733 | 0.97 | 35000 | 7.9496 | 18.9815 | 0.9228 |
| 0.9035 | 1.11 | 40000 | 7.689 | 18.9795 | 0.9162 |
| 0.9386 | 1.25 | 45000 | 7.6781 | 18.9825 | 0.9039 |
| 0.9073 | 1.39 | 50000 | 7.8607 | 18.9805 | 0.8986 |
| 0.8928 | 1.53 | 55000 | 8.0666 | 18.981 | 0.8942 |
| 0.884 | 1.67 | 60000 | 8.1679 | 18.9785 | 0.8874 |
| 0.8786 | 1.81 | 65000 | 7.8516 | 18.9805 | 0.8831 |
| 0.8899 | 1.95 | 70000 | 0.8789 | 7.9392 | 18.9785 |
| 0.8638 | 2.09 | 75000 | 0.8781 | 8.1623 | 18.979 |
| 0.8293 | 2.22 | 80000 | 0.8752 | 8.0989 | 18.98 |
| 0.8625 | 2.36 | 85000 | 0.8743 | 8.176 | 18.979 |
| 0.8605 | 2.5 | 90000 | 0.8721 | 8.0117 | 18.9805 |
| 0.8479 | 2.64 | 95000 | 0.8711 | 8.1008 | 18.978 |
| 0.8391 | 2.78 | 100000 | 0.8708 | 8.2041 | 18.9795 |
| 0.8649 | 2.92 | 105000 | 0.8710 | 8.1488 | 18.9785 |
### Framework versions
- Transformers 4.37.1
- Pytorch 2.1.2+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1
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