metadata
base_model: meta-llama/Llama-2-13b-hf
tags:
- generated_from_trainer
model-index:
- name: radiopaedia-inst_240215-llama2_13b-240215
results: []
radiopaedia-inst_240215-llama2_13b-240215
This model is a fine-tuned version of 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