falcon-7b-alpaca
This model is a fine-tuned version of tiiuae/falcon-7b-instruct on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.9657
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: 2e-05
- train_batch_size: 6
- eval_batch_size: 6
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 24
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 1
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
1.3865 | 0.0631 | 50 | 1.4032 |
1.2768 | 0.1262 | 100 | 1.2262 |
1.021 | 0.1893 | 150 | 1.0728 |
1.0843 | 0.2524 | 200 | 1.0175 |
0.9927 | 0.3155 | 250 | 0.9966 |
0.9746 | 0.3785 | 300 | 0.9836 |
1.02 | 0.4416 | 350 | 0.9767 |
0.9806 | 0.5047 | 400 | 0.9722 |
1.0579 | 0.5678 | 450 | 0.9684 |
1.0075 | 0.6309 | 500 | 0.9670 |
0.9909 | 0.6940 | 550 | 0.9661 |
0.9792 | 0.7571 | 600 | 0.9661 |
0.9449 | 0.8202 | 650 | 0.9654 |
0.9268 | 0.8833 | 700 | 0.9656 |
1.0441 | 0.9464 | 750 | 0.9657 |
Framework versions
- PEFT 0.11.1
- Transformers 4.41.0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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