---
license: apache-2.0
base_model: t5-small
tags:
- generated_from_trainer
metrics:
- bleu
model-index:
- name: en-vi-model_v3_opus
  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. -->

# en-vi-model_v3_opus

This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8572
- Bleu: 8.2434

## 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: 0.0005
- train_batch_size: 128
- eval_batch_size: 128
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step  | Bleu   | Validation Loss |
|:-------------:|:-----:|:-----:|:------:|:---------------:|
| 1.4493        | 0.13  | 500   | 3.9998 | 1.3541          |
| 1.2915        | 0.26  | 1000  | 5.3936 | 1.2113          |
| 1.2059        | 0.38  | 1500  | 5.8381 | 1.1367          |
| 1.1573        | 0.51  | 2000  | 6.2422 | 1.0901          |
| 1.1121        | 0.64  | 2500  | 6.6271 | 1.0542          |
| 1.0867        | 0.77  | 3000  | 6.8796 | 1.0252          |
| 1.0623        | 0.9   | 3500  | 7.0393 | 1.0068          |
| 1.0408        | 1.02  | 4000  | 7.2660 | 0.9882          |
| 1.0203        | 1.15  | 4500  | 7.0553 | 0.9723          |
| 1.0054        | 1.28  | 5000  | 7.4555 | 0.9624          |
| 0.9977        | 1.41  | 5500  | 7.4260 | 0.9526          |
| 0.9931        | 1.54  | 6000  | 7.5231 | 0.9396          |
| 0.9804        | 1.66  | 6500  | 7.4376 | 0.9324          |
| 0.9691        | 1.79  | 7000  | 7.5227 | 0.9264          |
| 0.9645        | 1.92  | 7500  | 7.6859 | 0.9193          |
| 0.9509        | 2.05  | 8000  | 7.6473 | 0.9144          |
| 0.9485        | 2.18  | 8500  | 7.6548 | 0.9118          |
| 0.9437        | 2.3   | 9000  | 7.6066 | 0.9073          |
| 0.9393        | 2.43  | 9500  | 7.7140 | 0.9019          |
| 0.9336        | 2.56  | 10000 | 7.8095 | 0.8970          |
| 0.9368        | 2.69  | 10500 | 7.9377 | 0.8937          |
| 0.925         | 2.82  | 11000 | 7.8425 | 0.8898          |
| 0.921         | 2.94  | 11500 | 7.9008 | 0.8864          |
| 0.9177        | 3.07  | 12000 | 7.9134 | 0.8836          |
| 0.9151        | 3.2   | 12500 | 0.8821 | 7.8647          |
| 0.9104        | 3.33  | 13000 | 0.8790 | 8.0830          |
| 0.9035        | 3.46  | 13500 | 0.8766 | 8.0959          |
| 0.8992        | 3.58  | 14000 | 0.8741 | 8.0178          |
| 0.8986        | 3.71  | 14500 | 0.8720 | 8.0384          |
| 0.894         | 3.84  | 15000 | 0.8683 | 8.0913          |
| 0.8932        | 3.97  | 15500 | 0.8663 | 8.0997          |
| 0.8889        | 4.1   | 16000 | 0.8641 | 8.1088          |
| 0.8888        | 4.22  | 16500 | 0.8629 | 8.0665          |
| 0.8856        | 4.35  | 17000 | 0.8607 | 8.2836          |
| 0.8826        | 4.48  | 17500 | 0.8613 | 8.2354          |
| 0.8862        | 4.61  | 18000 | 0.8578 | 8.1166          |
| 0.8811        | 4.74  | 18500 | 0.8583 | 8.1473          |
| 0.8799        | 4.86  | 19000 | 0.8579 | 8.1836          |
| 0.8827        | 4.99  | 19500 | 0.8572 | 8.2434          |


### Framework versions

- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1