---
base_model: meta-llama/Llama-2-13b-hf
tags:
- generated_from_trainer
model-index:
- name: radiopaedia_cl-llama2_13b-240311
  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. -->

# radiopaedia_cl-llama2_13b-240311

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: 0.7476

## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 0.8773        | 0.05  | 20   | 0.8701          |
| 0.8515        | 0.11  | 40   | 0.8439          |
| 0.8288        | 0.16  | 60   | 0.8311          |
| 0.8047        | 0.21  | 80   | 0.8179          |
| 0.7462        | 0.27  | 100  | 0.8031          |
| 0.852         | 0.32  | 120  | 0.7854          |
| 0.8301        | 0.37  | 140  | 0.7937          |
| 0.8407        | 0.42  | 160  | 0.7798          |
| 0.7099        | 0.48  | 180  | 0.7690          |
| 0.8138        | 0.53  | 200  | 0.7630          |
| 0.8015        | 0.58  | 220  | 0.7670          |
| 0.6831        | 0.64  | 240  | 0.7592          |
| 0.7111        | 0.69  | 260  | 0.7601          |
| 0.6946        | 0.74  | 280  | 0.7461          |
| 0.6754        | 0.8   | 300  | 0.7514          |
| 0.8267        | 0.85  | 320  | 0.7388          |
| 0.7297        | 0.9   | 340  | 0.7372          |
| 0.6722        | 0.96  | 360  | 0.7306          |
| 0.5094        | 1.01  | 380  | 0.7278          |
| 0.49          | 1.06  | 400  | 0.7530          |
| 0.5015        | 1.12  | 420  | 0.7643          |
| 0.4161        | 1.17  | 440  | 0.7585          |
| 0.5348        | 1.22  | 460  | 0.7661          |
| 0.4794        | 1.27  | 480  | 0.7525          |
| 0.4915        | 1.33  | 500  | 0.7573          |
| 0.4564        | 1.38  | 520  | 0.7667          |
| 0.5295        | 1.43  | 540  | 0.7640          |
| 0.503         | 1.49  | 560  | 0.7604          |
| 0.3933        | 1.54  | 580  | 0.7602          |
| 0.4384        | 1.59  | 600  | 0.7655          |
| 0.406         | 1.65  | 620  | 0.7531          |
| 0.5174        | 1.7   | 640  | 0.7473          |
| 0.4811        | 1.75  | 660  | 0.7457          |
| 0.4586        | 1.81  | 680  | 0.7519          |
| 0.4957        | 1.86  | 700  | 0.7469          |
| 0.4006        | 1.91  | 720  | 0.7458          |
| 0.454         | 1.97  | 740  | 0.7476          |


### Framework versions

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