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---
base_model: meta-llama/Llama-2-13b-hf
tags:
- generated_from_trainer
model-index:
- name: radiopaedia-inst_240215-llama2_13b-240215
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_240215-llama2_13b-240215
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: 0.7504
## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 0.851 | 0.05 | 20 | 0.8541 |
| 0.8377 | 0.11 | 40 | 0.8270 |
| 0.795 | 0.16 | 60 | 0.8237 |
| 0.7699 | 0.21 | 80 | 0.8089 |
| 0.953 | 0.27 | 100 | 0.7974 |
| 0.6894 | 0.32 | 120 | 0.7884 |
| 0.8883 | 0.37 | 140 | 0.7836 |
| 0.8814 | 0.42 | 160 | 0.7792 |
| 0.8322 | 0.48 | 180 | 0.7668 |
| 0.783 | 0.53 | 200 | 0.7745 |
| 0.6963 | 0.58 | 220 | 0.7683 |
| 0.7508 | 0.64 | 240 | 0.7540 |
| 0.7326 | 0.69 | 260 | 0.7582 |
| 0.7751 | 0.74 | 280 | 0.7501 |
| 0.6995 | 0.8 | 300 | 0.7473 |
| 0.7759 | 0.85 | 320 | 0.7428 |
| 0.6506 | 0.9 | 340 | 0.7383 |
| 0.7285 | 0.96 | 360 | 0.7296 |
| 0.5833 | 1.01 | 380 | 0.7347 |
| 0.5223 | 1.06 | 400 | 0.7535 |
| 0.3866 | 1.12 | 420 | 0.7685 |
| 0.4375 | 1.17 | 440 | 0.7586 |
| 0.4582 | 1.22 | 460 | 0.7539 |
| 0.4946 | 1.27 | 480 | 0.7646 |
| 0.5255 | 1.33 | 500 | 0.7670 |
| 0.4355 | 1.38 | 520 | 0.7581 |
| 0.4287 | 1.43 | 540 | 0.7574 |
| 0.478 | 1.49 | 560 | 0.7602 |
| 0.4236 | 1.54 | 580 | 0.7590 |
| 0.4873 | 1.59 | 600 | 0.7602 |
| 0.5377 | 1.65 | 620 | 0.7582 |
| 0.4546 | 1.7 | 640 | 0.7556 |
| 0.444 | 1.75 | 660 | 0.7539 |
| 0.3584 | 1.81 | 680 | 0.7526 |
| 0.4446 | 1.86 | 700 | 0.7502 |
| 0.385 | 1.91 | 720 | 0.7506 |
| 0.5061 | 1.97 | 740 | 0.7504 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.0.1+cu117
- Datasets 2.14.6
- Tokenizers 0.14.1
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