IE_L3_1000steps_1e5rate_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: 2.5960
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: 1e-05
- 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: 1000
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
1.5579 | 0.4 | 50 | 1.5074 |
1.6682 | 0.8 | 100 | 1.5842 |
1.1462 | 1.2 | 150 | 1.6953 |
1.1094 | 1.6 | 200 | 1.7268 |
1.1658 | 2.0 | 250 | 1.6667 |
0.4474 | 2.4 | 300 | 1.9842 |
0.437 | 2.8 | 350 | 1.9593 |
0.1509 | 3.2 | 400 | 2.1876 |
0.1546 | 3.6 | 450 | 2.2019 |
0.1572 | 4.0 | 500 | 2.1880 |
0.0608 | 4.4 | 550 | 2.3708 |
0.0654 | 4.8 | 600 | 2.3631 |
0.0315 | 5.2 | 650 | 2.5034 |
0.0311 | 5.6 | 700 | 2.4365 |
0.0315 | 6.0 | 750 | 2.4699 |
0.0235 | 6.4 | 800 | 2.5549 |
0.0193 | 6.8 | 850 | 2.5882 |
0.017 | 7.2 | 900 | 2.5931 |
0.0179 | 7.6 | 950 | 2.5959 |
0.0163 | 8.0 | 1000 | 2.5960 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.0.0+cu117
- Datasets 3.0.0
- Tokenizers 0.19.1
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Model tree for tsavage68/IE_L3_1000steps_1e5rate_SFT
Base model
meta-llama/Meta-Llama-3-8B-Instruct