mistral_7b_lora_completion_only
This model is a fine-tuned version of mistralai/Mistral-7B-Instruct-v0.2 on the DandinPower/ZH-Reading-Comprehension-Mistral-Instruct dataset. It achieves the following results on the evaluation set:
- Loss: 0.1344
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: 0.0001
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- total_eval_batch_size: 2
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 700
- num_epochs: 3.0
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
0.1996 | 0.3690 | 250 | 0.1814 |
0.1856 | 0.7380 | 500 | 0.1344 |
0.1515 | 1.1070 | 750 | 0.1724 |
0.1547 | 1.4760 | 1000 | 0.1977 |
0.0953 | 1.8450 | 1250 | 0.1641 |
0.0788 | 2.2140 | 1500 | 0.1450 |
0.0715 | 2.5830 | 1750 | 0.1359 |
0.0646 | 2.9520 | 2000 | 0.1427 |
Framework versions
- PEFT 0.10.0
- Transformers 4.40.0
- Pytorch 2.2.2+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1
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Model tree for DandinPower/mistral_7b_lora_completion_only
Base model
mistralai/Mistral-7B-Instruct-v0.2