V0224P6
This model is a fine-tuned version of yahma/llama-7b-hf on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.7620
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: 0.0003
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 32
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine_with_restarts
- lr_scheduler_warmup_steps: 20
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
1.085 | 0.13 | 10 | 1.0269 |
0.9547 | 0.26 | 20 | 0.9054 |
0.8742 | 0.39 | 30 | 0.8555 |
0.8306 | 0.52 | 40 | 0.8292 |
0.8157 | 0.65 | 50 | 0.8145 |
0.8024 | 0.78 | 60 | 0.8040 |
0.7797 | 0.91 | 70 | 0.7959 |
0.77 | 1.04 | 80 | 0.7861 |
0.7427 | 1.17 | 90 | 0.7787 |
0.7945 | 1.3 | 100 | 0.8105 |
0.7863 | 1.43 | 110 | 0.7969 |
0.7692 | 1.55 | 120 | 0.7881 |
0.7529 | 1.68 | 130 | 0.7809 |
0.761 | 1.81 | 140 | 0.7746 |
0.7638 | 1.94 | 150 | 0.7692 |
0.7401 | 2.07 | 160 | 0.7682 |
0.7216 | 2.2 | 170 | 0.7656 |
0.7336 | 2.33 | 180 | 0.7641 |
0.7245 | 2.46 | 190 | 0.7634 |
0.7252 | 2.59 | 200 | 0.7629 |
0.7279 | 2.72 | 210 | 0.7622 |
0.7258 | 2.85 | 220 | 0.7621 |
0.7271 | 2.98 | 230 | 0.7620 |
Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.14.1
Model tree for Litzy619/V0224P6
Base model
yahma/llama-7b-hf