|
--- |
|
base_model: meta-llama/Llama-2-13b-hf |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: Llama-2-13b-lr-5e-5 |
|
results: [] |
|
--- |
|
|
|
<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
|
should probably proofread and complete it, then remove this comment. --> |
|
|
|
# Llama-2-13b-lr-5e-5 |
|
|
|
This model is a fine-tuned version of [meta-llama/Llama-2-13b-hf](https://huggingface.co/meta-llama/Llama-2-13b-hf) on the None dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 1.1454 |
|
- Accuracy: 0.2150 |
|
|
|
## 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: 5e-05 |
|
- train_batch_size: 2 |
|
- eval_batch_size: 2 |
|
- seed: 42 |
|
- distributed_type: multi-GPU |
|
- num_devices: 16 |
|
- total_train_batch_size: 32 |
|
- total_eval_batch_size: 32 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: cosine |
|
- lr_scheduler_warmup_ratio: 0.03 |
|
- num_epochs: 3.0 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:| |
|
| 0.955 | 0.37 | 10 | 0.9061 | 0.2182 | |
|
| 0.8899 | 0.74 | 20 | 0.8734 | 0.2196 | |
|
| 0.879 | 1.11 | 30 | 0.9091 | 0.2174 | |
|
| 0.3295 | 1.48 | 40 | 0.9803 | 0.2173 | |
|
| 0.3711 | 1.85 | 50 | 0.9820 | 0.2174 | |
|
| 0.2927 | 2.22 | 60 | 1.0270 | 0.2153 | |
|
| 0.1703 | 2.59 | 70 | 1.0966 | 0.2131 | |
|
| 0.2011 | 2.96 | 80 | 1.1488 | 0.2145 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.35.2 |
|
- Pytorch 2.1.0+cu121 |
|
- Datasets 2.15.0 |
|
- Tokenizers 0.15.0 |
|
|
