transformers safetensors llama text-generation generated_from_trainer base_model:meta-llama/Llama-2-13b-hf autotrain_compatible endpoints_compatible text-generation-inference region:us
---
base_model: meta-llama/Llama-2-13b-hf
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: Llama-2-13b-lr-5e-5
  results: []
---

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# 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
