transformers pytorch t5 text2text-generation generated_from_trainer dataset:opus_books base_model:google-t5/t5-base base_model:finetune:google-t5/t5-base license:apache-2.0 model-index autotrain_compatible text-generation-inference endpoints_compatible region:us
---
base_model: t5-base
datasets:
- opus_books
license: apache-2.0
metrics:
- bleu
tags:
- generated_from_trainer
model-index:
- name: translation_1
  results:
  - task:
      type: text2text-generation
      name: Sequence-to-sequence Language Modeling
    dataset:
      name: opus_books
      type: opus_books
      config: en-ru
      split: train
      args: en-ru
    metrics:
    - type: bleu
      value: 5.03
      name: Bleu
---

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# translation_1

This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on the opus_books dataset.
It achieves the following results on the evaluation set:
- Loss: 2.5005
- Bleu: 5.03
- Gen Len: 16.0434

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Bleu   | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:-------:|
| 3.4771        | 1.0   | 875   | 2.8863          | 2.2211 | 16.4083 |
| 2.9851        | 2.0   | 1750  | 2.7086          | 3.2474 | 16.4271 |
| 2.8137        | 3.0   | 2625  | 2.6050          | 3.8481 | 16.378  |
| 2.6962        | 4.0   | 3500  | 2.5268          | 4.3032 | 16.2734 |
| 2.6439        | 5.0   | 4375  | 2.4694          | 4.5354 | 16.2414 |
| 2.5633        | 6.0   | 5250  | 2.4227          | 4.8672 | 16.2483 |
| 2.5122        | 7.0   | 6125  | 2.4068          | 5.0916 | 16.256  |
| 2.693         | 8.0   | 7000  | 2.5069          | 5.0708 | 16.0449 |
| 2.6754        | 9.0   | 7875  | 2.5003          | 5.0422 | 16.0389 |
| 2.6714        | 10.0  | 8750  | 2.5003          | 5.0467 | 16.0357 |
| 2.6679        | 11.0  | 9625  | 2.5003          | 5.0482 | 16.038  |
| 2.6812        | 12.0  | 10500 | 2.5004          | 5.0456 | 16.0377 |
| 2.6733        | 13.0  | 11375 | 2.5004          | 5.0456 | 16.036  |
| 2.6802        | 14.0  | 12250 | 2.5005          | 5.0454 | 16.0403 |
| 2.6652        | 15.0  | 13125 | 2.5005          | 5.0403 | 16.0391 |
| 2.6718        | 16.0  | 14000 | 2.5005          | 5.0483 | 16.0403 |
| 2.6756        | 17.0  | 14875 | 2.5005          | 5.0324 | 16.04   |
| 2.6751        | 18.0  | 15750 | 2.5005          | 5.03   | 16.0434 |
| 2.6689        | 19.0  | 16625 | 2.5005          | 5.03   | 16.0434 |
| 2.6687        | 20.0  | 17500 | 2.5005          | 5.03   | 16.0434 |


### Framework versions

- Transformers 4.33.2
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.13.3
