Seamless M4T – FLEURS Indic Multilingual Fine‑tuning
This model is a fine-tuned version of facebook/seamless-m4t-v2-large on the FLEURS dataset.
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: 32
- eval_batch_size: 16
- seed: 42
- optimizer: Use adafactor and the args are: No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 25
- training_steps: 925
Training results
Framework versions
- Transformers 4.48.3
- Pytorch 2.6.0+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0
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Model tree for jonahdvt/seamless-m4t-fleurs-indic
Base model
facebook/seamless-m4t-v2-large