MentaLLaMA-chat-7B-PsyCourse-doc-info-fold4
This model is a fine-tuned version of klyang/MentaLLaMA-chat-7B-hf on the course-doc-info-train-fold4 dataset. It achieves the following results on the evaluation set:
- Loss: 0.0882
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 |
---|---|---|---|
0.3967 | 0.3951 | 10 | 0.4004 |
0.4552 | 0.7901 | 20 | 0.2511 |
0.1757 | 1.1852 | 30 | 0.1820 |
0.1409 | 1.5802 | 40 | 0.1474 |
0.1122 | 1.9753 | 50 | 0.1285 |
0.2986 | 2.3704 | 60 | 0.1134 |
0.0918 | 2.7654 | 70 | 0.1039 |
0.0807 | 3.1605 | 80 | 0.0966 |
0.0862 | 3.5556 | 90 | 0.0924 |
0.085 | 3.9506 | 100 | 0.0891 |
0.101 | 4.3457 | 110 | 0.0883 |
0.0736 | 4.7407 | 120 | 0.0882 |
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