---
base_model: meta-llama/Llama-2-13b-hf
tags:
- generated_from_trainer
model-index:
- name: radiopaedia-inst_240219-llama2_13b-240220
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# radiopaedia-inst_240219-llama2_13b-240220

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: 0.7007

## 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: 0.0003
- train_batch_size: 8
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 10
- num_epochs: 2
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.8308        | 0.05  | 20   | 0.7775          |
| 0.767         | 0.11  | 40   | 0.7579          |
| 0.7219        | 0.16  | 60   | 0.7441          |
| 0.6127        | 0.21  | 80   | 0.7489          |
| 0.6799        | 0.27  | 100  | 0.7415          |
| 0.7201        | 0.32  | 120  | 0.7369          |
| 0.7045        | 0.37  | 140  | 0.7298          |
| 0.7259        | 0.42  | 160  | 0.7190          |
| 0.8055        | 0.48  | 180  | 0.7158          |
| 0.6834        | 0.53  | 200  | 0.7066          |
| 0.7885        | 0.58  | 220  | 0.7111          |
| 0.71          | 0.64  | 240  | 0.7003          |
| 0.7124        | 0.69  | 260  | 0.7008          |
| 0.6625        | 0.74  | 280  | 0.7052          |
| 0.691         | 0.8   | 300  | 0.6925          |
| 0.6148        | 0.85  | 320  | 0.6915          |
| 0.6727        | 0.9   | 340  | 0.6821          |
| 0.5608        | 0.96  | 360  | 0.6777          |
| 0.5981        | 1.01  | 380  | 0.6786          |
| 0.5295        | 1.06  | 400  | 0.7046          |
| 0.4217        | 1.12  | 420  | 0.7027          |
| 0.4026        | 1.17  | 440  | 0.7211          |
| 0.4469        | 1.22  | 460  | 0.7030          |
| 0.3774        | 1.27  | 480  | 0.7153          |
| 0.5217        | 1.33  | 500  | 0.7175          |
| 0.3966        | 1.38  | 520  | 0.6978          |
| 0.4662        | 1.43  | 540  | 0.7010          |
| 0.4038        | 1.49  | 560  | 0.6971          |
| 0.4514        | 1.54  | 580  | 0.7009          |
| 0.423         | 1.59  | 600  | 0.7069          |
| 0.3961        | 1.65  | 620  | 0.7030          |
| 0.3723        | 1.7   | 640  | 0.7008          |
| 0.3745        | 1.75  | 660  | 0.7008          |
| 0.4442        | 1.81  | 680  | 0.7087          |
| 0.4094        | 1.86  | 700  | 0.7040          |
| 0.3465        | 1.91  | 720  | 0.7015          |
| 0.3751        | 1.97  | 740  | 0.7007          |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.0.1+cu117
- Datasets 2.14.6
- Tokenizers 0.14.1