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---
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
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