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---
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
should probably proofread and complete it, then remove this comment. -->
# 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
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