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---
library_name: transformers
tags:
- generated_from_trainer
datasets:
- gokulsrinivasagan/processed_book_corpus-ld-20
metrics:
- accuracy
model-index:
- name: distilbert_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: 0.7289610693406705
---
<!-- 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. -->
# distilbert_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: 3.5714
- Accuracy: 0.7290
## 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: 96
- eval_batch_size: 96
- 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 |
|:-------------:|:-------:|:------:|:---------------:|:--------:|
| 7.2789 | 0.4215 | 10000 | 6.5733 | 0.3678 |
| 4.955 | 0.8431 | 20000 | 4.5929 | 0.5844 |
| 4.6182 | 1.2646 | 30000 | 4.3014 | 0.6199 |
| 4.4751 | 1.6861 | 40000 | 4.1692 | 0.6387 |
| 4.3802 | 2.1077 | 50000 | 4.0856 | 0.6498 |
| 4.3162 | 2.5292 | 60000 | 4.0203 | 0.6598 |
| 4.2637 | 2.9507 | 70000 | 3.9798 | 0.6658 |
| 4.225 | 3.3723 | 80000 | 3.9419 | 0.6716 |
| 4.1939 | 3.7938 | 90000 | 3.9101 | 0.6761 |
| 4.1637 | 4.2153 | 100000 | 3.8892 | 0.6795 |
| 4.1428 | 4.6369 | 110000 | 3.8674 | 0.6830 |
| 4.1204 | 5.0584 | 120000 | 3.8432 | 0.6860 |
| 4.1028 | 5.4799 | 130000 | 3.8268 | 0.6887 |
| 4.091 | 5.9014 | 140000 | 3.8095 | 0.6912 |
| 4.0686 | 6.3230 | 150000 | 3.7973 | 0.6936 |
| 4.0613 | 6.7445 | 160000 | 3.7854 | 0.6952 |
| 4.0375 | 7.1660 | 170000 | 3.7712 | 0.6976 |
| 4.0301 | 7.5876 | 180000 | 3.7640 | 0.6984 |
| 4.0202 | 8.0091 | 190000 | 3.7519 | 0.7002 |
| 4.0102 | 8.4306 | 200000 | 3.7429 | 0.7018 |
| 3.9985 | 8.8522 | 210000 | 3.7357 | 0.7031 |
| 3.9959 | 9.2737 | 220000 | 3.7270 | 0.7044 |
| 3.9781 | 9.6952 | 230000 | 3.7161 | 0.7058 |
| 3.9676 | 10.1168 | 240000 | 3.7122 | 0.7069 |
| 3.9672 | 10.5383 | 250000 | 3.7028 | 0.7080 |
| 3.9573 | 10.9598 | 260000 | 3.6969 | 0.7093 |
| 3.9497 | 11.3814 | 270000 | 3.6923 | 0.7098 |
| 3.9483 | 11.8029 | 280000 | 3.6841 | 0.7111 |
| 3.9348 | 12.2244 | 290000 | 3.6786 | 0.7119 |
| 3.9304 | 12.6460 | 300000 | 3.6703 | 0.7132 |
| 3.9205 | 13.0675 | 310000 | 3.6666 | 0.7139 |
| 3.9202 | 13.4890 | 320000 | 3.6620 | 0.7146 |
| 3.9152 | 13.9106 | 330000 | 3.6581 | 0.7152 |
| 3.9105 | 14.3321 | 340000 | 3.6501 | 0.7167 |
| 3.9024 | 14.7536 | 350000 | 3.6466 | 0.7168 |
| 3.8976 | 15.1751 | 360000 | 3.6444 | 0.7173 |
| 3.8948 | 15.5967 | 370000 | 3.6362 | 0.7186 |
| 3.8875 | 16.0182 | 380000 | 3.6316 | 0.7193 |
| 3.8842 | 16.4397 | 390000 | 3.6280 | 0.7199 |
| 3.8773 | 16.8613 | 400000 | 3.6256 | 0.7203 |
| 3.8766 | 17.2828 | 410000 | 3.6190 | 0.7214 |
| 3.8712 | 17.7043 | 420000 | 3.6155 | 0.7220 |
| 3.8638 | 18.1259 | 430000 | 3.6134 | 0.7225 |
| 3.8588 | 18.5474 | 440000 | 3.6109 | 0.7228 |
| 3.8586 | 18.9689 | 450000 | 3.6057 | 0.7237 |
| 3.8534 | 19.3905 | 460000 | 3.6018 | 0.7241 |
| 3.8508 | 19.8120 | 470000 | 3.5988 | 0.7247 |
| 3.8443 | 20.2335 | 480000 | 3.5953 | 0.7252 |
| 3.8393 | 20.6551 | 490000 | 3.5921 | 0.7257 |
| 3.8366 | 21.0766 | 500000 | 3.5886 | 0.7260 |
| 3.8324 | 21.4981 | 510000 | 3.5857 | 0.7266 |
| 3.8286 | 21.9197 | 520000 | 3.5843 | 0.7269 |
| 3.8317 | 22.3412 | 530000 | 3.5818 | 0.7273 |
| 3.8243 | 22.7627 | 540000 | 3.5811 | 0.7276 |
| 3.825 | 23.1843 | 550000 | 3.5771 | 0.7279 |
| 3.8227 | 23.6058 | 560000 | 3.5752 | 0.7284 |
| 3.8173 | 24.0273 | 570000 | 3.5741 | 0.7286 |
| 3.8174 | 24.4488 | 580000 | 3.5706 | 0.7291 |
| 3.8141 | 24.8704 | 590000 | 3.5708 | 0.7289 |
### Framework versions
- Transformers 4.46.3
- Pytorch 2.2.1+cu118
- Datasets 2.17.0
- Tokenizers 0.20.3
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