---
license: apache-2.0
base_model: t5-small
tags:
- generated_from_trainer
datasets:
- opus100
metrics:
- bleu
model-index:
- name: GenzTranscribe-en-gu
  results:
  - task:
      name: Sequence-to-sequence Language Modeling
      type: text2text-generation
    dataset:
      name: opus100
      type: opus100
      config: en-gu
      split: train
      args: en-gu
    metrics:
    - name: Bleu
      type: bleu
      value: 59.9227
---

<!-- 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. -->

# GenzTranscribe-en-gu

This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the opus100 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3075
- Bleu: 59.9227
- Gen Len: 9.6443

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Bleu    | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|
| 0.3593        | 1.0   | 31831 | 0.3253          | 58.1921 | 9.7108  |
| 0.3421        | 2.0   | 63662 | 0.3075          | 59.9227 | 9.6443  |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.1
- Tokenizers 0.13.3