Quick Links
opus-mt-en-es-finetuned
This model is a fine-tuned version of Helsinki-NLP/opus-mt-en-es on an Helsinki-NLP/opus-100 en-es dataset. It achieves the following results on the evaluation set:
- Loss: 1.2279
- Bleu: 43.9648
- Chrf++: 62.5724
- Gen Len: 17.9065
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu | Chrf++ | Gen Len |
|---|---|---|---|---|---|---|
| 1.2527 | 1.0 | 62500 | 1.2411 | 43.1812 | 62.1134 | 17.89 |
| 1.1721 | 2.0 | 125000 | 1.2335 | 43.5934 | 62.3235 | 17.9905 |
| 1.1064 | 3.0 | 187500 | 1.2279 | 43.9663 | 62.5747 | 17.9125 |
Framework versions
- Transformers 5.0.0
- Pytorch 2.10.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2
- Downloads last month
- 7
Inference Providers NEW
This model isn't deployed by any Inference Provider. 🙋 Ask for provider support
Model tree for marymary2000/opus-mt-en-es-finetuned
Base model
Helsinki-NLP/opus-mt-en-es
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("marymary2000/opus-mt-en-es-finetuned") model = AutoModelForSeq2SeqLM.from_pretrained("marymary2000/opus-mt-en-es-finetuned", device_map="auto")