---
library_name: transformers
license: apache-2.0
base_model: google-t5/t5-base
tags:
- generated_from_trainer
metrics:
- bleu
model-index:
- name: elvish-translator-quenya-t5-base
  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. -->

# elvish-translator-quenya-t5-base

This model is a fine-tuned version of [google-t5/t5-base](https://huggingface.co/google-t5/t5-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 3.4619
- Bleu: 0.3386
- Gen Len: 14.3889

## 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: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Bleu   | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|
| 4.5969        | 1.0   | 144  | 4.0271          | 0.1511 | 14.5278 |
| 4.1388        | 2.0   | 288  | 3.8283          | 0.1435 | 15.3819 |
| 3.9458        | 3.0   | 432  | 3.7158          | 0.2337 | 13.2639 |
| 3.808         | 4.0   | 576  | 3.6417          | 0.2594 | 14.0278 |
| 3.7546        | 5.0   | 720  | 3.5761          | 0.295  | 14.7639 |
| 3.6707        | 6.0   | 864  | 3.5284          | 0.2913 | 15.2986 |
| 3.6004        | 7.0   | 1008 | 3.4973          | 0.3018 | 14.9861 |
| 3.5505        | 8.0   | 1152 | 3.4758          | 0.3043 | 14.7431 |
| 3.5129        | 9.0   | 1296 | 3.4659          | 0.3296 | 14.4792 |
| 3.5232        | 10.0  | 1440 | 3.4619          | 0.3386 | 14.3889 |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.2.1+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1