Na_L3_600steps_1e7rate_SFT
This model is a fine-tuned version of meta-llama/Meta-Llama-3-8B-Instruct on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.0537
Model description
More information needed
Intended uses & limitations
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Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-07
- train_batch_size: 2
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 100
- training_steps: 600
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
2.8904 | 0.2667 | 50 | 2.8306 |
2.5711 | 0.5333 | 100 | 2.4828 |
2.0286 | 0.8 | 150 | 1.9826 |
1.6431 | 1.0667 | 200 | 1.6198 |
1.4055 | 1.3333 | 250 | 1.3752 |
1.2427 | 1.6 | 300 | 1.2211 |
1.1406 | 1.8667 | 350 | 1.1275 |
1.0808 | 2.1333 | 400 | 1.0817 |
1.0548 | 2.4 | 450 | 1.0596 |
1.0453 | 2.6667 | 500 | 1.0556 |
1.0558 | 2.9333 | 550 | 1.0537 |
1.0493 | 3.2 | 600 | 1.0537 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
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Base model
meta-llama/Meta-Llama-3-8B-Instruct