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e2m_denoise_finetuned
This model is a fine-tuned version of smitmenon/e2m_endenoise_project on the flores dataset. It achieves the following results on the evaluation set:
- Loss: 0.5925
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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.609 | 1.0 | 125 | 0.5857 |
| 0.4397 | 2.0 | 250 | 0.5925 |
Framework versions
- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0
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facebook/mbart-large-50-one-to-many-mmt Finetuned
smitmenon/e2m_endenoise_project
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("smitmenon/e2m_denoise_finetuned") model = AutoModelForSeq2SeqLM.from_pretrained("smitmenon/e2m_denoise_finetuned")