File size: 4,979 Bytes
011f5a4 1ecd0de 011f5a4 6da886a 011f5a4 6da886a 011f5a4 e4595aa 011f5a4 e4595aa 011f5a4 |
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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 |
---
library_name: peft
license: llama3.1
base_model: meta-llama/Llama-3.1-8B-Instruct
tags:
- llama-factory
- lora
- generated_from_trainer
model-index:
- name: Llama-3.1-8B-Instruct-PsyCourse-fold3
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. -->
# Llama-3.1-8B-Instruct-PsyCourse-fold3
This model is a fine-tuned version of [meta-llama/Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Llama-3.1-8B-Instruct) on the course-train-fold3 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0352
## 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 |
|:-------------:|:------:|:----:|:---------------:|
| 0.5742 | 0.0753 | 50 | 0.4037 |
| 0.0981 | 0.1505 | 100 | 0.0890 |
| 0.0775 | 0.2258 | 150 | 0.0663 |
| 0.075 | 0.3011 | 200 | 0.0574 |
| 0.0587 | 0.3763 | 250 | 0.0533 |
| 0.0617 | 0.4516 | 300 | 0.0547 |
| 0.0431 | 0.5269 | 350 | 0.0519 |
| 0.0573 | 0.6021 | 400 | 0.0479 |
| 0.0504 | 0.6774 | 450 | 0.0438 |
| 0.0341 | 0.7527 | 500 | 0.0428 |
| 0.0448 | 0.8279 | 550 | 0.0440 |
| 0.0373 | 0.9032 | 600 | 0.0414 |
| 0.0369 | 0.9785 | 650 | 0.0414 |
| 0.0266 | 1.0537 | 700 | 0.0422 |
| 0.0337 | 1.1290 | 750 | 0.0380 |
| 0.0379 | 1.2043 | 800 | 0.0424 |
| 0.0297 | 1.2795 | 850 | 0.0413 |
| 0.0417 | 1.3548 | 900 | 0.0389 |
| 0.0342 | 1.4300 | 950 | 0.0393 |
| 0.033 | 1.5053 | 1000 | 0.0387 |
| 0.0304 | 1.5806 | 1050 | 0.0412 |
| 0.0225 | 1.6558 | 1100 | 0.0380 |
| 0.0406 | 1.7311 | 1150 | 0.0359 |
| 0.0314 | 1.8064 | 1200 | 0.0378 |
| 0.0345 | 1.8816 | 1250 | 0.0352 |
| 0.0314 | 1.9569 | 1300 | 0.0352 |
| 0.0232 | 2.0322 | 1350 | 0.0370 |
| 0.0298 | 2.1074 | 1400 | 0.0358 |
| 0.0224 | 2.1827 | 1450 | 0.0376 |
| 0.0251 | 2.2580 | 1500 | 0.0403 |
| 0.0303 | 2.3332 | 1550 | 0.0377 |
| 0.0174 | 2.4085 | 1600 | 0.0399 |
| 0.02 | 2.4838 | 1650 | 0.0393 |
| 0.0239 | 2.5590 | 1700 | 0.0386 |
| 0.0377 | 2.6343 | 1750 | 0.0377 |
| 0.0266 | 2.7096 | 1800 | 0.0373 |
| 0.0229 | 2.7848 | 1850 | 0.0356 |
| 0.0257 | 2.8601 | 1900 | 0.0409 |
| 0.021 | 2.9354 | 1950 | 0.0365 |
| 0.0137 | 3.0106 | 2000 | 0.0382 |
| 0.0119 | 3.0859 | 2050 | 0.0439 |
| 0.0116 | 3.1612 | 2100 | 0.0427 |
| 0.0131 | 3.2364 | 2150 | 0.0435 |
| 0.0132 | 3.3117 | 2200 | 0.0436 |
| 0.0095 | 3.3870 | 2250 | 0.0448 |
| 0.0101 | 3.4622 | 2300 | 0.0486 |
| 0.0068 | 3.5375 | 2350 | 0.0472 |
| 0.0133 | 3.6128 | 2400 | 0.0447 |
| 0.0155 | 3.6880 | 2450 | 0.0423 |
| 0.0118 | 3.7633 | 2500 | 0.0446 |
| 0.0104 | 3.8386 | 2550 | 0.0464 |
| 0.0149 | 3.9138 | 2600 | 0.0434 |
| 0.0126 | 3.9891 | 2650 | 0.0439 |
| 0.0066 | 4.0644 | 2700 | 0.0464 |
| 0.0048 | 4.1396 | 2750 | 0.0502 |
| 0.0052 | 4.2149 | 2800 | 0.0543 |
| 0.0051 | 4.2901 | 2850 | 0.0537 |
| 0.0102 | 4.3654 | 2900 | 0.0547 |
| 0.0052 | 4.4407 | 2950 | 0.0546 |
| 0.0029 | 4.5159 | 3000 | 0.0548 |
| 0.0085 | 4.5912 | 3050 | 0.0552 |
| 0.0049 | 4.6665 | 3100 | 0.0551 |
| 0.0054 | 4.7417 | 3150 | 0.0553 |
| 0.0035 | 4.8170 | 3200 | 0.0553 |
| 0.0041 | 4.8923 | 3250 | 0.0554 |
| 0.0045 | 4.9675 | 3300 | 0.0553 |
### Framework versions
- PEFT 0.12.0
- Transformers 4.46.1
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.20.3 |