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---
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
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