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mbart oscar-hindi text generator
This model is a fine-tuned version of facebook/mbart-large-50-many-to-many-mmt on the oscar dataset. It achieves the following results on the evaluation set:
- Loss: 3.8315
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: 3.0
Training results
Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0
- Downloads last month
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Model tree for guldasta/mbart-oscar-hindi-gen
Base model
facebook/mbart-large-50-many-to-many-mmt
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("guldasta/mbart-oscar-hindi-gen") model = AutoModelForSeq2SeqLM.from_pretrained("guldasta/mbart-oscar-hindi-gen")