How to use from the
Use from the
Transformers library
# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("Ro551/m2m100_418M-GEC-spanish-LORA-synthetic", device_map="auto")
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m2m100_418M-GEC-spanish-LORA-synthetic

This model is a fine-tuned version of facebook/m2m100_418M on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 3.9074
  • Gleu: 0.9276

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: 0.00044107500561578277
  • train_batch_size: 16
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Use OptimizerNames.ADAFACTOR and the args are: No additional optimizer arguments
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 0.08950396527674138
  • num_epochs: 2
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Gleu
3.9485 1.0 6896 3.9114 0.9166
3.9632 2.0 13792 3.9074 0.9276

Framework versions

  • PEFT 0.18.1
  • Transformers 5.0.0
  • Pytorch 2.7.0+cu126
  • Datasets 4.8.5
  • Tokenizers 0.22.2
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