File size: 4,067 Bytes
bd074a1 |
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 |
---
base_model: facebook/bart-large-cnn
library_name: peft
license: mit
tags:
- generated_from_trainer
model-index:
- name: lora_fine_tuned_bart
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. -->
[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/nedith22-makerere-university/Fatima%20Fellowahip2024/runs/pvowwaid)
# lora_fine_tuned_bart
This model is a fine-tuned version of [facebook/bart-large-cnn](https://huggingface.co/facebook/bart-large-cnn) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6906
## 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: 4e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.7253 | 1.0 | 32 | 1.8719 |
| 1.426 | 2.0 | 64 | 1.6167 |
| 1.3662 | 3.0 | 96 | 1.5225 |
| 1.3049 | 4.0 | 128 | 1.4695 |
| 1.2084 | 5.0 | 160 | 1.4319 |
| 1.2666 | 6.0 | 192 | 1.3709 |
| 1.2344 | 7.0 | 224 | 1.3053 |
| 1.1056 | 8.0 | 256 | 1.2560 |
| 1.025 | 9.0 | 288 | 1.1773 |
| 0.915 | 10.0 | 320 | 1.0743 |
| 0.8726 | 11.0 | 352 | 1.0085 |
| 0.8281 | 12.0 | 384 | 0.9630 |
| 0.777 | 13.0 | 416 | 0.9116 |
| 0.7681 | 14.0 | 448 | 0.8817 |
| 0.664 | 15.0 | 480 | 0.8357 |
| 0.6604 | 16.0 | 512 | 0.8077 |
| 0.6351 | 17.0 | 544 | 0.7837 |
| 0.6455 | 18.0 | 576 | 0.7724 |
| 0.6167 | 19.0 | 608 | 0.7585 |
| 0.5969 | 20.0 | 640 | 0.7443 |
| 0.5605 | 21.0 | 672 | 0.7382 |
| 0.5835 | 22.0 | 704 | 0.7302 |
| 0.5668 | 23.0 | 736 | 0.7183 |
| 0.575 | 24.0 | 768 | 0.7124 |
| 0.5319 | 25.0 | 800 | 0.7129 |
| 0.5515 | 26.0 | 832 | 0.7085 |
| 0.5219 | 27.0 | 864 | 0.7119 |
| 0.5509 | 28.0 | 896 | 0.7074 |
| 0.5172 | 29.0 | 928 | 0.7014 |
| 0.5298 | 30.0 | 960 | 0.7034 |
| 0.5071 | 31.0 | 992 | 0.6930 |
| 0.525 | 32.0 | 1024 | 0.6941 |
| 0.5153 | 33.0 | 1056 | 0.6963 |
| 0.5115 | 34.0 | 1088 | 0.6925 |
| 0.5194 | 35.0 | 1120 | 0.6933 |
| 0.5138 | 36.0 | 1152 | 0.6926 |
| 0.4649 | 37.0 | 1184 | 0.6913 |
| 0.5127 | 38.0 | 1216 | 0.6932 |
| 0.5044 | 39.0 | 1248 | 0.6929 |
| 0.4701 | 40.0 | 1280 | 0.6921 |
| 0.5156 | 41.0 | 1312 | 0.6931 |
| 0.5163 | 42.0 | 1344 | 0.6898 |
| 0.5153 | 43.0 | 1376 | 0.6896 |
| 0.5054 | 44.0 | 1408 | 0.6880 |
| 0.4915 | 45.0 | 1440 | 0.6872 |
| 0.4908 | 46.0 | 1472 | 0.6879 |
| 0.4836 | 47.0 | 1504 | 0.6891 |
| 0.491 | 48.0 | 1536 | 0.6889 |
| 0.4814 | 49.0 | 1568 | 0.6905 |
| 0.4872 | 50.0 | 1600 | 0.6906 |
### Framework versions
- PEFT 0.12.0
- Transformers 4.42.3
- Pytorch 2.1.2
- Datasets 2.20.0
- Tokenizers 0.19.1 |