Mistral7BInstruct-lora-classifier-test
This model is a fine-tuned version of mistralai/Mistral-7B-Instruct-v0.3 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 245.375
- Accuracy: 0.5667
- F1 Macro: 0.4937
- F1 Weighted: 0.4645
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: 0.02
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 128
- optimizer: Use paged_adamw_8bit with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | F1 Weighted |
|---|---|---|---|---|---|---|
| No log | 1.0 | 1 | 8.6797 | 0.3333 | 0.1754 | 0.1930 |
| No log | 2.0 | 2 | 191.5 | 0.5667 | 0.4693 | 0.4514 |
| No log | 3.0 | 3 | 284.5 | 0.3333 | 0.1667 | 0.1667 |
| No log | 4.0 | 4 | 255.875 | 0.5 | 0.4286 | 0.4048 |
| No log | 5.0 | 5 | 245.375 | 0.5667 | 0.4937 | 0.4645 |
Framework versions
- PEFT 0.17.1
- Transformers 4.52.4
- Pytorch 2.6.0+cu124
- Datasets 4.1.1
- Tokenizers 0.21.4
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Model tree for nhatha2004/Mistral7BInstruct-lora-classifier-test
Base model
mistralai/Mistral-7B-v0.3 Finetuned
mistralai/Mistral-7B-Instruct-v0.3