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

This model is a fine-tuned version of [google-t5/t5-small](https://huggingface.co/google-t5/t5-small) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 3.9119
- Bleu: 0.1206
- Gen Len: 16.6875

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|
| 4.9376        | 1.0   | 144  | 4.3320          | 0.1122 | 16.9514 |
| 4.5062        | 2.0   | 288  | 4.1559          | 0.1191 | 15.9653 |
| 4.3624        | 3.0   | 432  | 4.0699          | 0.1118 | 16.7361 |
| 4.2832        | 4.0   | 576  | 4.0222          | 0.1474 | 16.3125 |
| 4.2286        | 5.0   | 720  | 3.9854          | 0.1421 | 16.2778 |
| 4.1762        | 6.0   | 864  | 3.9550          | 0.1107 | 16.9583 |
| 4.14          | 7.0   | 1008 | 3.9386          | 0.1215 | 16.1944 |
| 4.087         | 8.0   | 1152 | 3.9221          | 0.1232 | 16.7153 |
| 4.0988        | 9.0   | 1296 | 3.9154          | 0.1206 | 16.6875 |
| 4.0738        | 10.0  | 1440 | 3.9119          | 0.1206 | 16.6875 |


### Framework versions

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