---
base_model: meta-llama/Llama-2-7b-hf
tags:
- generated_from_trainer
model-index:
- name: llama_finetune_mc_20
  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_finetune_mc_20

This model is a fine-tuned version of [meta-llama/Llama-2-7b-hf](https://huggingface.co/meta-llama/Llama-2-7b-hf) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 4.4015

## 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: 0.0001
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 5
- num_epochs: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.9393        | 1.0   | 70   | 1.8240          |
| 0.2414        | 2.0   | 140  | 2.5937          |
| 0.126         | 3.0   | 210  | 2.8429          |
| 0.0836        | 4.0   | 280  | 2.9219          |
| 0.0872        | 5.0   | 350  | 3.2516          |
| 0.0575        | 6.0   | 420  | 3.1180          |
| 0.0482        | 7.0   | 490  | 3.4019          |
| 0.0356        | 8.0   | 560  | 3.3709          |
| 0.0305        | 9.0   | 630  | 3.5186          |
| 0.0272        | 10.0  | 700  | 3.8218          |
| 0.0243        | 11.0  | 770  | 3.7827          |
| 0.0312        | 12.0  | 840  | 3.9016          |
| 0.0259        | 13.0  | 910  | 4.0432          |
| 0.027         | 14.0  | 980  | 4.1255          |
| 0.0205        | 15.0  | 1050 | 4.1950          |
| 0.0199        | 16.0  | 1120 | 4.2793          |
| 0.0219        | 17.0  | 1190 | 4.3363          |
| 0.0197        | 18.0  | 1260 | 4.3627          |
| 0.0218        | 19.0  | 1330 | 4.3868          |
| 0.0201        | 20.0  | 1400 | 4.4015          |


### Framework versions

- Transformers 4.36.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.13.1
- Tokenizers 0.14.1