finetuned-model / README.md
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---
license: apache-2.0
base_model: Helsinki-NLP/opus-mt-en-es
tags:
- generated_from_trainer
datasets:
- kde4
metrics:
- bleu
model-index:
- name: finetuned-model
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: kde4
type: kde4
config: en-es
split: train
args: en-es
metrics:
- name: Bleu
type: bleu
value: 42.22590503762825
---
<!-- 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. -->
# finetuned-model
This model is a fine-tuned version of [Helsinki-NLP/opus-mt-en-es](https://huggingface.co./Helsinki-NLP/opus-mt-en-es) on the kde4 dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0902
- Bleu: 42.2259
- Bert Score: 0.9004
## 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: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
### Training results
### Framework versions
- Transformers 4.34.1
- Pytorch 2.0.1
- Datasets 2.14.6
- Tokenizers 0.14.1