llama_7b_hf_relu_refined_web_relu_2024-03-26
This model is a fine-tuned version of meta-llama/Llama-2-7b-hf on the None dataset. It achieves the following results on the evaluation set:
- Loss: 3.6081
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: 1
- eval_batch_size: 1
- seed: 0
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- total_eval_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 200
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
9.5465 | 0.02 | 25 | 9.1446 |
7.7377 | 0.03 | 50 | 7.5825 |
6.5903 | 0.05 | 75 | 6.3866 |
5.4942 | 0.06 | 100 | 5.3487 |
4.6502 | 0.08 | 125 | 4.6675 |
4.2062 | 0.1 | 150 | 4.2042 |
3.7988 | 0.11 | 175 | 3.8759 |
3.5327 | 0.13 | 200 | 3.6560 |
Framework versions
- Transformers 4.36.2
- Pytorch 2.1.1+cu121
- Datasets 2.15.0
- Tokenizers 0.15.2
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Model tree for thrunlab/llama_7b_hf_relu_refined_web_relu_2024-03-26
Base model
meta-llama/Llama-2-7b-hf