Mistral-7B-Instruct-v0.3-lora-commonsense
This model is a fine-tuned version of mistralai/Mistral-7B-Instruct-v0.3 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6863
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: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 100
- num_epochs: 3
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
0.8738 | 0.1503 | 200 | 0.8158 |
0.8589 | 0.3006 | 400 | 0.7939 |
0.8589 | 0.4510 | 600 | 0.7800 |
0.8589 | 0.6013 | 800 | 0.7725 |
0.8305 | 0.7516 | 1000 | 0.7650 |
0.8331 | 0.9019 | 1200 | 0.7506 |
0.7808 | 1.0522 | 1400 | 0.7438 |
0.7781 | 1.2026 | 1600 | 0.7350 |
0.7647 | 1.3529 | 1800 | 0.7252 |
0.7651 | 1.5032 | 2000 | 0.7228 |
0.7522 | 1.6535 | 2200 | 0.7099 |
0.7587 | 1.8038 | 2400 | 0.6997 |
0.7383 | 1.9542 | 2600 | 0.6932 |
0.7071 | 2.1045 | 2800 | 0.6949 |
0.6919 | 2.2548 | 3000 | 0.6899 |
0.7136 | 2.4051 | 3200 | 0.6884 |
0.6912 | 2.5554 | 3400 | 0.6878 |
0.6889 | 2.7057 | 3600 | 0.6867 |
0.6862 | 2.8561 | 3800 | 0.6863 |
Framework versions
- Transformers 4.42.3
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
Model tree for yspkm/Mistral-7B-Instruct-v0.3-lora-commonsense
Base model
mistralai/Mistral-7B-v0.3
Finetuned
mistralai/Mistral-7B-Instruct-v0.3