---
base_model: meta-llama/Llama-2-7b-hf
tags:
- generated_from_trainer
model-index:
- name: llama_7b_hf_relu_refined_web_relu_2024-03-26
  results: []
---

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# llama_7b_hf_relu_refined_web_relu_2024-03-26

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: 3.6081

## 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