MentaLLaMA-chat-7B-PsyCourse-info-fold5
This model is a fine-tuned version of klyang/MentaLLaMA-chat-7B-hf on the course-info-train-fold5 dataset. It achieves the following results on the evaluation set:
- Loss: 0.1536
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
- gradient_accumulation_steps: 16
- total_train_batch_size: 16
- optimizer: Use adamw_torch 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: 5.0
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
0.7894 | 0.3951 | 10 | 0.6199 |
0.3067 | 0.7901 | 20 | 0.2628 |
0.1744 | 1.1852 | 30 | 0.1975 |
0.1489 | 1.5802 | 40 | 0.1722 |
0.1622 | 1.9753 | 50 | 0.1676 |
0.1611 | 2.3704 | 60 | 0.1615 |
0.1067 | 2.7654 | 70 | 0.1636 |
0.0909 | 3.1605 | 80 | 0.1559 |
0.0873 | 3.5556 | 90 | 0.1536 |
0.0842 | 3.9506 | 100 | 0.1546 |
0.0893 | 4.3457 | 110 | 0.1551 |
0.1005 | 4.7407 | 120 | 0.1554 |
Framework versions
- PEFT 0.12.0
- Transformers 4.46.1
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.20.3
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Base model
klyang/MentaLLaMA-chat-7B-hf