robbert-v2-dutch-base-finetuned-emotion-arousal

This model is a fine-tuned version of pdelobelle/robbert-v2-dutch-base on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.0230
• Rmse: 0.1517

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: 2e-05
• train_batch_size: 32
• eval_batch_size: 32
• 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	Rmse
0.0581	1.0	25	0.0349	0.1868
0.0355	2.0	50	0.0340	0.1845
0.0295	3.0	75	0.0271	0.1645
0.0288	4.0	100	0.0279	0.1670
0.0277	5.0	125	0.0316	0.1777
0.0254	6.0	150	0.0263	0.1620
0.0193	7.0	175	0.0247	0.1571
0.0173	8.0	200	0.0304	0.1745
0.0179	9.0	225	0.0239	0.1547
0.0149	10.0	250	0.0244	0.1563
0.0134	11.0	275	0.0248	0.1576
0.0113	12.0	300	0.0256	0.1601
0.0112	13.0	325	0.0265	0.1627
0.0114	14.0	350	0.0299	0.1730
0.0111	15.0	375	0.0268	0.1638
0.0098	16.0	400	0.0256	0.1599
0.009	17.0	425	0.0252	0.1588
0.0078	18.0	450	0.0256	0.1601
0.0093	19.0	475	0.0235	0.1532
0.009	20.0	500	0.0246	0.1568
0.0084	21.0	525	0.0238	0.1543
0.0083	22.0	550	0.0255	0.1598
0.0074	23.0	575	0.0250	0.1582
0.0079	24.0	600	0.0248	0.1574
0.0077	25.0	625	0.0261	0.1616
0.0073	26.0	650	0.0261	0.1615
0.0071	27.0	675	0.0247	0.1571
0.0068	28.0	700	0.0254	0.1593
0.0062	29.0	725	0.0250	0.1581
0.006	30.0	750	0.0255	0.1597
0.0066	31.0	775	0.0241	0.1553
0.0064	32.0	800	0.0242	0.1555
0.006	33.0	825	0.0240	0.1549
0.0055	34.0	850	0.0244	0.1561
0.0055	35.0	875	0.0235	0.1533
0.0053	36.0	900	0.0241	0.1551
0.0056	37.0	925	0.0238	0.1542
0.0052	38.0	950	0.0248	0.1576
0.0055	39.0	975	0.0247	0.1570
0.0054	40.0	1000	0.0233	0.1526
0.0052	41.0	1025	0.0233	0.1525
0.0048	42.0	1050	0.0231	0.1519
0.0051	43.0	1075	0.0237	0.1538
0.0051	44.0	1100	0.0231	0.1520
0.0053	45.0	1125	0.0234	0.1531
0.0046	46.0	1150	0.0230	0.1517
0.0049	47.0	1175	0.0230	0.1518
0.005	48.0	1200	0.0230	0.1518
0.0047	49.0	1225	0.0237	0.1540
0.0047	50.0	1250	0.0230	0.1517

Framework versions

• Transformers 4.42.4
• Pytorch 2.3.1+cu121
• Datasets 2.20.0
• Tokenizers 0.19.1