fine-tuned-BioBARTv2-20-epochs-1024-input-288-output

tanatapanun/fine-tuned-BioBARTv2-20-epochs-1024-input-288-output

fine-tuned-BioBARTv2-20-epochs-1024-input-288-output is a machine learning model from tanatapanun. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers.

should probably proofread and complete it, then remove this comment. --

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At a glance

Library: transformers
Model type: bart
Access: Public
Created: Jan 29, 2024
Updated: Jan 29, 2024
SHA: aaba68d5

Base models

checkpoint_global_step_200000

Model card

From the Hugging Face model README

fine-tuned-BioBARTv2-20-epochs-1024-input-288-output

This model is a fine-tuned version of checkpoint_global_step_200000 on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.8737
Rouge1: 0.1792
Rouge2: 0.0323
Rougel: 0.1391
Rougelsum: 0.1399
Gen Len: 36.3

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: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 20

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
No log	1.0	151	6.4453	0.0289	0.0003	0.0283	0.0278	21.32
No log	2.0	302	1.0350	0.1165	0.0335	0.0969	0.0965	34.35
No log	3.0	453	0.8905	0.0745	0.0151	0.0539	0.0545	32.84
4.1419	4.0	604	0.8387	0.1225	0.0334	0.0911	0.0909	31.01
4.1419	5.0	755	0.8139	0.17	0.0335	0.1343	0.1339	53.7
4.1419	6.0	906	0.8070	0.1165	0.0242	0.0936	0.0916	26.25
0.7039	7.0	1057	0.7982	0.1367	0.0299	0.0998	0.1007	43.94
0.7039	8.0	1208	0.7926	0.1689	0.0408	0.1265	0.1276	47.35
0.7039	9.0	1359	0.8005	0.1603	0.0336	0.1338	0.1335	31.24
0.4936	10.0	1510	0.8062	0.1641	0.0358	0.1256	0.1254	33.11
0.4936	11.0	1661	0.8085	0.1934	0.0437	0.1527	0.1542	42.14
0.4936	12.0	1812	0.8143	0.1699	0.0398	0.1304	0.1301	49.52
0.4936	13.0	1963	0.8348	0.1619	0.0272	0.1263	0.1262	31.8
0.352	14.0	2114	0.8365	0.2093	0.0485	0.1657	0.1667	42.77
0.352	15.0	2265	0.8455	0.168	0.0345	0.1298	0.131	35.95
0.352	16.0	2416	0.8532	0.1953	0.048	0.1546	0.1561	37.21
0.2569	17.0	2567	0.8604	0.1834	0.0359	0.1431	0.1442	39.24
0.2569	18.0	2718	0.8702	0.1628	0.029	0.1209	0.1217	35.94
0.2569	19.0	2869	0.8712	0.1792	0.04	0.1382	0.139	37.38
0.211	20.0	3020	0.8737	0.1792	0.0323	0.1391	0.1399	36.3

Framework versions

Transformers 4.36.2
Pytorch 1.12.1+cu113
Datasets 2.16.1
Tokenizers 0.15.1

Library: transformers
Type: bart
Created: Jan 29, 2024
Updated: Jan 29, 2024