---
base_model: meta-llama/Llama-2-7b-hf
tags:
- generated_from_trainer
model-index:
- name: llama_7b_hf_relu_refined_web_relu_2024-03-27
  results: []
---

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# llama_7b_hf_relu_refined_web_relu_2024-03-27

This model is a fine-tuned version of [meta-llama/Llama-2-7b-hf](https://huggingface.co/meta-llama/Llama-2-7b-hf) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 3.6599

## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 9.5817        | 0.01  | 25   | 9.2314          |
| 7.8754        | 0.02  | 50   | 7.6756          |
| 6.6513        | 0.02  | 75   | 6.5579          |
| 5.5276        | 0.03  | 100  | 5.4724          |
| 4.8802        | 0.04  | 125  | 4.7672          |
| 4.1435        | 0.05  | 150  | 4.2747          |
| 3.7831        | 0.06  | 175  | 3.9269          |
| 3.6802        | 0.06  | 200  | 3.6937          |


### Framework versions

- Transformers 4.40.0.dev0
- Pytorch 2.1.1+cu121
- Datasets 2.15.0
- Tokenizers 0.15.2