translation_llm
This model is a fine-tuned version of NousResearch/Llama-2-7b-hf on an dataset that combines russian sentences from two datasets: parallel-sentences-tatoeba and parallel-sentences-wikimatrix. The model is finetuned for russian language.
It achieves the following results on the evaluation set:
- Loss: 0.0039
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: 0.0002
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 32
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.0063 | 0.8591 | 1000 | 0.0110 |
| 0.0041 | 1.7181 | 2000 | 0.0089 |
| 0.0016 | 2.5772 | 3000 | 0.0086 |
| 0.0006 | 3.4362 | 4000 | 0.0041 |
| 0.0023 | 4.2953 | 5000 | 0.0039 |
Framework versions
- PEFT 0.13.0
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1
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Base model
NousResearch/Llama-2-7b-hf