V0224O8
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: 0.7624
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 |
---|---|---|---|
3.9612 | 0.13 | 10 | 2.0439 |
1.4314 | 0.26 | 20 | 1.1580 |
1.0339 | 0.39 | 30 | 0.9539 |
0.9046 | 0.52 | 40 | 0.8871 |
0.8662 | 0.65 | 50 | 0.8508 |
0.8339 | 0.78 | 60 | 0.8298 |
0.8019 | 0.91 | 70 | 0.8141 |
0.7904 | 1.04 | 80 | 0.8041 |
0.7626 | 1.17 | 90 | 0.7947 |
0.776 | 1.3 | 100 | 0.7878 |
0.7619 | 1.43 | 110 | 0.7824 |
0.7509 | 1.55 | 120 | 0.7770 |
0.7403 | 1.68 | 130 | 0.7742 |
0.7502 | 1.81 | 140 | 0.7708 |
0.7532 | 1.94 | 150 | 0.7675 |
0.7299 | 2.07 | 160 | 0.7672 |
0.7119 | 2.2 | 170 | 0.7657 |
0.7218 | 2.33 | 180 | 0.7639 |
0.7146 | 2.46 | 190 | 0.7636 |
0.7166 | 2.59 | 200 | 0.7633 |
0.7191 | 2.72 | 210 | 0.7626 |
0.7164 | 2.85 | 220 | 0.7624 |
0.7177 | 2.98 | 230 | 0.7624 |
Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.14.1
Model tree for Litzy619/V0224O8
Base model
yahma/llama-7b-hf