File size: 3,779 Bytes
e5eb4de c3a9631 e5eb4de c3a9631 e5eb4de c3a9631 e5eb4de |
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 |
---
license: other
base_model: microsoft/phi-1_5
tags:
- generated_from_trainer
model-index:
- name: phi-1_5-psychology
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. -->
# phi-1_5-psychology
This model is a fine-tuned version of [microsoft/phi-1_5](https://huggingface.co/microsoft/phi-1_5) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7574
## 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: 0.0002
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.8667 | 0.04 | 100 | 0.8554 |
| 0.8401 | 0.09 | 200 | 0.8524 |
| 0.8492 | 0.13 | 300 | 0.8437 |
| 0.8563 | 0.18 | 400 | 0.8393 |
| 0.8353 | 0.22 | 500 | 0.8367 |
| 0.8232 | 0.26 | 600 | 0.8305 |
| 0.8299 | 0.31 | 700 | 0.8226 |
| 0.8307 | 0.35 | 800 | 0.8233 |
| 0.8087 | 0.39 | 900 | 0.8170 |
| 0.8124 | 0.44 | 1000 | 0.8160 |
| 0.7943 | 0.48 | 1100 | 0.8103 |
| 0.7924 | 0.53 | 1200 | 0.8076 |
| 0.7918 | 0.57 | 1300 | 0.8026 |
| 0.807 | 0.61 | 1400 | 0.8012 |
| 0.788 | 0.66 | 1500 | 0.8034 |
| 0.7946 | 0.7 | 1600 | 0.7946 |
| 0.7959 | 0.75 | 1700 | 0.7926 |
| 0.7878 | 0.79 | 1800 | 0.7921 |
| 0.754 | 0.83 | 1900 | 0.7890 |
| 0.7762 | 0.88 | 2000 | 0.7850 |
| 0.7651 | 0.92 | 2100 | 0.7849 |
| 0.7868 | 0.97 | 2200 | 0.7855 |
| 0.7651 | 1.01 | 2300 | 0.7820 |
| 0.7323 | 1.05 | 2400 | 0.7818 |
| 0.7316 | 1.1 | 2500 | 0.7804 |
| 0.7311 | 1.14 | 2600 | 0.7808 |
| 0.7221 | 1.18 | 2700 | 0.7782 |
| 0.722 | 1.23 | 2800 | 0.7736 |
| 0.7217 | 1.27 | 2900 | 0.7780 |
| 0.7226 | 1.32 | 3000 | 0.7730 |
| 0.7305 | 1.36 | 3100 | 0.7731 |
| 0.7237 | 1.4 | 3200 | 0.7712 |
| 0.7127 | 1.45 | 3300 | 0.7710 |
| 0.7252 | 1.49 | 3400 | 0.7699 |
| 0.7076 | 1.54 | 3500 | 0.7687 |
| 0.7185 | 1.58 | 3600 | 0.7672 |
| 0.6921 | 1.62 | 3700 | 0.7639 |
| 0.6882 | 1.67 | 3800 | 0.7642 |
| 0.7184 | 1.71 | 3900 | 0.7633 |
| 0.7048 | 1.76 | 4000 | 0.7601 |
| 0.7136 | 1.8 | 4100 | 0.7598 |
| 0.7063 | 1.84 | 4200 | 0.7591 |
| 0.7054 | 1.89 | 4300 | 0.7589 |
| 0.6945 | 1.93 | 4400 | 0.7564 |
| 0.6955 | 1.97 | 4500 | 0.7544 |
| 0.6869 | 2.02 | 4600 | 0.7536 |
| 0.6477 | 2.06 | 4700 | 0.7566 |
| 0.6593 | 2.11 | 4800 | 0.7568 |
| 0.6441 | 2.15 | 4900 | 0.7562 |
| 0.6527 | 2.19 | 5000 | 0.7574 |
### Framework versions
- Transformers 4.33.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
|