Model Card for Model ID
Adapter for mlsquare/pico_seshu_test using LoRA on "model.layers.3.dt_proj", "model.layers.3.x_proj", "model.layers.3.out_proj". Standard use of PEFT on Mamba-hf model
Model Details
Model Description
- Developed by: MLsquare
- Model type: Next Character Generation
- Language(s) (NLP): All languages in ai4bharat/samanantar dataset
- License: MIT
Model Details
Model Description
- Developed by: MLsquare
- Model type: Next Character Generation
- Language(s) (NLP): All languages in ai4bharat/samanantar dataset
- License: MIT
Model Sources [optional]
- Repository: https://github.com/LegallyCoder/mamba-hf
- Paper: https://arxiv.org/abs/2312.00752
Uses
Refer to the github repository for more information
Direct Use
Refer to the github repository for more information
How to Get Started with the Model
Refer to the github repository: https://github.com/mlsquare/fedem
Training Details
Training Data
Individual target and source sentences from the AI4Bharat Samanantar dataset. All 11 language sentences and their translations have been stacked and used for next character generation task.
Training Procedure
Trained on the next character generation task using cross-entropy loss.
Preprocessing [optional]
converted to raw UTF8 characters before training by using ByT5-large tokenizer
Training Hyperparameters
- Training regime: output_dir="mamba", per_device_train_batch_size=1, per_device_eval_batch_size=1, num_train_epochs=4, weight_decay=0.1, lr_scheduler_type="cosine", learning_rate=5e-4, fp16=False,
Evaluation
A simple cross-entropy loss has been used to test the pipeline and working of the model.
Model Card Contact
MLsquare