File size: 4,911 Bytes
d028943 9102bba d028943 9102bba d028943 9102bba d028943 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 |
---
library_name: peft
license: llama3
base_model: aaditya/Llama3-OpenBioLLM-8B
tags:
- llama-factory
- lora
- generated_from_trainer
model-index:
- name: Llama3-OpenBioLLM-8B-PsyCourse-fold4
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. -->
# Llama3-OpenBioLLM-8B-PsyCourse-fold4
This model is a fine-tuned version of [aaditya/Llama3-OpenBioLLM-8B](https://huggingface.co/aaditya/Llama3-OpenBioLLM-8B) on the course-train-fold4 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0349
## 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: 0.0001
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 16
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5.0
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.4799 | 0.0763 | 50 | 0.2933 |
| 0.1053 | 0.1527 | 100 | 0.0766 |
| 0.0594 | 0.2290 | 150 | 0.0722 |
| 0.0586 | 0.3053 | 200 | 0.0537 |
| 0.066 | 0.3816 | 250 | 0.0550 |
| 0.0553 | 0.4580 | 300 | 0.0551 |
| 0.0468 | 0.5343 | 350 | 0.0476 |
| 0.0515 | 0.6106 | 400 | 0.0481 |
| 0.0562 | 0.6870 | 450 | 0.0466 |
| 0.0347 | 0.7633 | 500 | 0.0401 |
| 0.0417 | 0.8396 | 550 | 0.0408 |
| 0.0466 | 0.9159 | 600 | 0.0393 |
| 0.0346 | 0.9923 | 650 | 0.0404 |
| 0.035 | 1.0686 | 700 | 0.0389 |
| 0.0408 | 1.1449 | 750 | 0.0390 |
| 0.0324 | 1.2213 | 800 | 0.0427 |
| 0.0331 | 1.2976 | 850 | 0.0382 |
| 0.0335 | 1.3739 | 900 | 0.0433 |
| 0.034 | 1.4502 | 950 | 0.0374 |
| 0.0253 | 1.5266 | 1000 | 0.0399 |
| 0.0299 | 1.6029 | 1050 | 0.0382 |
| 0.0534 | 1.6792 | 1100 | 0.0424 |
| 0.0318 | 1.7556 | 1150 | 0.0402 |
| 0.0484 | 1.8319 | 1200 | 0.0385 |
| 0.0263 | 1.9082 | 1250 | 0.0355 |
| 0.0329 | 1.9845 | 1300 | 0.0349 |
| 0.0171 | 2.0609 | 1350 | 0.0365 |
| 0.0204 | 2.1372 | 1400 | 0.0374 |
| 0.0248 | 2.2135 | 1450 | 0.0413 |
| 0.0132 | 2.2899 | 1500 | 0.0397 |
| 0.0152 | 2.3662 | 1550 | 0.0383 |
| 0.0222 | 2.4425 | 1600 | 0.0387 |
| 0.0187 | 2.5188 | 1650 | 0.0374 |
| 0.0177 | 2.5952 | 1700 | 0.0415 |
| 0.0164 | 2.6715 | 1750 | 0.0380 |
| 0.0212 | 2.7478 | 1800 | 0.0395 |
| 0.0248 | 2.8242 | 1850 | 0.0357 |
| 0.0187 | 2.9005 | 1900 | 0.0384 |
| 0.0315 | 2.9768 | 1950 | 0.0372 |
| 0.006 | 3.0531 | 2000 | 0.0423 |
| 0.0077 | 3.1295 | 2050 | 0.0459 |
| 0.0073 | 3.2058 | 2100 | 0.0493 |
| 0.0096 | 3.2821 | 2150 | 0.0523 |
| 0.0086 | 3.3585 | 2200 | 0.0449 |
| 0.0057 | 3.4348 | 2250 | 0.0469 |
| 0.0098 | 3.5111 | 2300 | 0.0460 |
| 0.0086 | 3.5874 | 2350 | 0.0493 |
| 0.0073 | 3.6638 | 2400 | 0.0471 |
| 0.0086 | 3.7401 | 2450 | 0.0468 |
| 0.0079 | 3.8164 | 2500 | 0.0455 |
| 0.0042 | 3.8928 | 2550 | 0.0473 |
| 0.0088 | 3.9691 | 2600 | 0.0474 |
| 0.004 | 4.0454 | 2650 | 0.0474 |
| 0.0033 | 4.1217 | 2700 | 0.0500 |
| 0.0009 | 4.1981 | 2750 | 0.0520 |
| 0.0021 | 4.2744 | 2800 | 0.0532 |
| 0.0042 | 4.3507 | 2850 | 0.0546 |
| 0.0017 | 4.4271 | 2900 | 0.0566 |
| 0.002 | 4.5034 | 2950 | 0.0577 |
| 0.0021 | 4.5797 | 3000 | 0.0583 |
| 0.0017 | 4.6560 | 3050 | 0.0585 |
| 0.0036 | 4.7324 | 3100 | 0.0587 |
| 0.0021 | 4.8087 | 3150 | 0.0588 |
| 0.0028 | 4.8850 | 3200 | 0.0588 |
| 0.0021 | 4.9614 | 3250 | 0.0588 |
### Framework versions
- PEFT 0.12.0
- Transformers 4.46.1
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.20.3 |