File size: 4,053 Bytes
9a0f34c 708b134 9a0f34c 708b134 9a0f34c 708b134 9a0f34c 708b134 9a0f34c |
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 |
---
library_name: transformers
tags:
- generated_from_trainer
datasets:
- gokulsrinivasagan/processed_book_corpus-ld-20
metrics:
- accuracy
model-index:
- name: bert_tiny_lda_20_v1_book
results:
- task:
name: Masked Language Modeling
type: fill-mask
dataset:
name: gokulsrinivasagan/processed_book_corpus-ld-20
type: gokulsrinivasagan/processed_book_corpus-ld-20
metrics:
- name: Accuracy
type: accuracy
value: 0.6793461178036027
---
<!-- 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. -->
# bert_tiny_lda_20_v1_book
This model is a fine-tuned version of [](https://huggingface.co/) on the gokulsrinivasagan/processed_book_corpus-ld-20 dataset.
It achieves the following results on the evaluation set:
- Loss: 3.8712
- Accuracy: 0.6793
## 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: 160
- eval_batch_size: 160
- seed: 10
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 10000
- num_epochs: 25
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:------:|:---------------:|:--------:|
| 8.6049 | 0.7025 | 10000 | 8.4377 | 0.1653 |
| 5.6593 | 1.4051 | 20000 | 5.2243 | 0.5031 |
| 5.1606 | 2.1076 | 30000 | 4.7778 | 0.5589 |
| 4.9169 | 2.8102 | 40000 | 4.5539 | 0.5885 |
| 4.7607 | 3.5127 | 50000 | 4.4085 | 0.6088 |
| 4.6405 | 4.2153 | 60000 | 4.3027 | 0.6216 |
| 4.5578 | 4.9178 | 70000 | 4.2156 | 0.6307 |
| 4.496 | 5.6203 | 80000 | 4.1619 | 0.6375 |
| 4.457 | 6.3229 | 90000 | 4.1256 | 0.6425 |
| 4.4199 | 7.0254 | 100000 | 4.0918 | 0.6468 |
| 4.3953 | 7.7280 | 110000 | 4.0677 | 0.6504 |
| 4.3703 | 8.4305 | 120000 | 4.0441 | 0.6538 |
| 4.3437 | 9.1331 | 130000 | 4.0295 | 0.6560 |
| 4.3295 | 9.8356 | 140000 | 4.0084 | 0.6594 |
| 4.3125 | 10.5381 | 150000 | 3.9955 | 0.6612 |
| 4.3048 | 11.2407 | 160000 | 3.9842 | 0.6627 |
| 4.2863 | 11.9432 | 170000 | 3.9727 | 0.6645 |
| 4.276 | 12.6458 | 180000 | 3.9592 | 0.6663 |
| 4.2651 | 13.3483 | 190000 | 3.9543 | 0.6669 |
| 4.2573 | 14.0509 | 200000 | 3.9438 | 0.6683 |
| 4.247 | 14.7534 | 210000 | 3.9343 | 0.6699 |
| 4.2387 | 15.4560 | 220000 | 3.9274 | 0.6712 |
| 4.2331 | 16.1585 | 230000 | 3.9226 | 0.6718 |
| 4.2238 | 16.8610 | 240000 | 3.9161 | 0.6727 |
| 4.2171 | 17.5636 | 250000 | 3.9106 | 0.6735 |
| 4.2098 | 18.2661 | 260000 | 3.9046 | 0.6740 |
| 4.2083 | 18.9687 | 270000 | 3.9001 | 0.6749 |
| 4.1991 | 19.6712 | 280000 | 3.8949 | 0.6759 |
| 4.1961 | 20.3738 | 290000 | 3.8903 | 0.6766 |
| 4.1893 | 21.0763 | 300000 | 3.8864 | 0.6772 |
| 4.1866 | 21.7788 | 310000 | 3.8808 | 0.6779 |
| 4.181 | 22.4814 | 320000 | 3.8782 | 0.6784 |
| 4.18 | 23.1839 | 330000 | 3.8763 | 0.6785 |
| 4.1771 | 23.8865 | 340000 | 3.8731 | 0.6790 |
| 4.1765 | 24.5890 | 350000 | 3.8704 | 0.6795 |
### Framework versions
- Transformers 4.46.3
- Pytorch 2.2.1+cu118
- Datasets 2.17.0
- Tokenizers 0.20.3
|