Mistral-7B-Instruct-v0.2-multilingual-deita-10k-v0-sft-v0.1
This model is a fine-tuned version of mistralai/Mistral-7B-Instruct-v0.2 on the nthakur/multilingual-deita-10k-v0-sft-v0.1 dataset. It achieves the following results on the evaluation set:
- Loss: 0.6604
Model description
More information needed
Intended uses & limitations
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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: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.8266 | 0.2861 | 200 | 0.6874 |
| 0.7478 | 0.5722 | 400 | 0.6693 |
| 0.7963 | 0.8584 | 600 | 0.6609 |
Framework versions
- PEFT 0.7.1
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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Model tree for nthakur/Mistral-7B-Instruct-v0.2-multilingual-deita-10k-v0-sft-v0.1
Base model
mistralai/Mistral-7B-Instruct-v0.2