TinyLlama-1.1B PO (MT)
Collection
TinyLlama-1.1B models fine-tuned models for machine translation
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TinyLlama-1.1B-MT-SLiC-DPO
This model is a fine-tuned version of martimfasantos/TinyLlama-1.1B-MT-SFT on the sardinelab/MT-pref 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: 1e-07
- train_batch_size: 1
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 32
- total_train_batch_size: 64
- total_eval_batch_size: 8
- optimizer: Adam with betas=(0.9,0.95) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3
Training results
Framework versions
- Transformers 4.43.3
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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Model tree for martimfasantos/TinyLlama-1.1B-MT-SLiC-DPO
Finetuned
martimfasantos/TinyLlama-1.1B-MT-SFT