bert_tiny_lda_5_v1_book

This model is a fine-tuned version of on the gokulsrinivasagan/processed_book_corpus-ld-5 dataset. It achieves the following results on the evaluation set:

• Loss: 2.8600
• Accuracy: 0.6858

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
7.2508	0.7025	10000	7.0913	0.1639
5.6868	1.4051	20000	5.0071	0.4074
4.0487	2.1076	30000	3.6967	0.5617
3.7657	2.8102	40000	3.4422	0.5989
3.6336	3.5127	50000	3.3142	0.6176
3.5449	4.2153	60000	3.2372	0.6291
3.4893	4.9178	70000	3.1788	0.6376
3.4397	5.6203	80000	3.1367	0.6442
3.4066	6.3229	90000	3.1054	0.6491
3.3758	7.0254	100000	3.0734	0.6534
3.3548	7.7280	110000	3.0504	0.6571
3.3302	8.4305	120000	3.0304	0.6599
3.3087	9.1331	130000	3.0157	0.6620
3.2942	9.8356	140000	2.9982	0.6654
3.2799	10.5381	150000	2.9831	0.6672
3.271	11.2407	160000	2.9750	0.6687
3.2545	11.9432	170000	2.9624	0.6703
3.2444	12.6458	180000	2.9493	0.6723
3.2336	13.3483	190000	2.9428	0.6731
3.2254	14.0509	200000	2.9316	0.6746
3.2143	14.7534	210000	2.9231	0.6759
3.2058	15.4560	220000	2.9154	0.6772
3.2014	16.1585	230000	2.9095	0.6780
3.1923	16.8610	240000	2.9047	0.6788
3.1846	17.5636	250000	2.8982	0.6797
3.1797	18.2661	260000	2.8922	0.6805
3.1768	18.9687	270000	2.8886	0.6813
3.1696	19.6712	280000	2.8828	0.6822
3.1656	20.3738	290000	2.8787	0.6826
3.1581	21.0763	300000	2.8756	0.6834
3.1566	21.7788	310000	2.8690	0.6842
3.1508	22.4814	320000	2.8671	0.6845
3.1496	23.1839	330000	2.8648	0.6849
3.1475	23.8865	340000	2.8612	0.6853
3.1459	24.5890	350000	2.8586	0.6859

Framework versions

• Transformers 4.46.3
• Pytorch 2.2.1+cu118
• Datasets 2.17.0
• Tokenizers 0.20.3