metadata
base_model: meta-llama/Llama-2-7b-hf
tags:
- generated_from_trainer
model-index:
- name: sparse_llama_7b_hf_refined_web_70p_2024-03-25
results: []
sparse_llama_7b_hf_refined_web_70p_2024-03-25
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: 2.2471
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: 4
- gradient_accumulation_steps: 8
- total_train_batch_size: 32
- total_eval_batch_size: 4
- 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 |
|---|---|---|---|
| 2.3676 | 0.01 | 25 | 2.5933 |
| 2.3572 | 0.02 | 50 | 2.5793 |
| 2.4503 | 0.02 | 75 | 2.5568 |
| 2.3803 | 0.03 | 100 | 2.5265 |
| 2.4451 | 0.04 | 125 | 2.4951 |
| 2.2793 | 0.05 | 150 | 2.4778 |
| 2.2444 | 0.06 | 175 | 2.4667 |
| 2.406 | 0.06 | 200 | 2.4572 |
Framework versions
- Transformers 4.36.2
- Pytorch 2.1.1+cu121
- Datasets 2.15.0
- Tokenizers 0.15.2