t5-small_winobias_finetuned

This model is a fine-tuned version of t5-small on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.2473
• Accuracy: 0.5278
• Tp: 0.5
• Tn: 0.0278
• Fp: 0.4722
• Fn: 0.0

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: 0.0003
• train_batch_size: 64
• eval_batch_size: 64
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 30

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Tp	Tn	Fp	Fn
0.6334	0.8	20	0.3622	0.5	0.5	0.0	0.5	0.0
0.4058	1.6	40	0.3510	0.5	0.5	0.0	0.5	0.0
0.3923	2.4	60	0.3511	0.5	0.5	0.0	0.5	0.0
0.376	3.2	80	0.3509	0.5	0.5	0.0	0.5	0.0
0.3749	4.0	100	0.3502	0.5	0.5	0.0	0.5	0.0
0.3895	4.8	120	0.3505	0.5	0.5	0.0	0.5	0.0
0.3624	5.6	140	0.3508	0.5	0.5	0.0	0.5	0.0
0.3754	6.4	160	0.3501	0.5	0.5	0.0	0.5	0.0
0.3702	7.2	180	0.3576	0.5	0.5	0.0	0.5	0.0
0.3748	8.0	200	0.3499	0.5	0.5	0.0	0.5	0.0
0.3715	8.8	220	0.3482	0.5	0.5	0.0	0.5	0.0
0.3576	9.6	240	0.3489	0.5	0.5	0.0	0.5	0.0
0.3659	10.4	260	0.3510	0.5	0.5	0.0	0.5	0.0
0.3565	11.2	280	0.3464	0.5	0.5	0.0	0.5	0.0
0.353	12.0	300	0.3474	0.5	0.5	0.0	0.5	0.0
0.3614	12.8	320	0.3450	0.5	0.5	0.0	0.5	0.0
0.3625	13.6	340	0.3458	0.5	0.5	0.0	0.5	0.0
0.36	14.4	360	0.3494	0.5	0.5	0.0	0.5	0.0
0.3585	15.2	380	0.3435	0.5	0.5	0.0	0.5	0.0
0.3541	16.0	400	0.3431	0.5	0.5	0.0	0.5	0.0
0.3564	16.8	420	0.3414	0.5	0.5	0.0	0.5	0.0
0.3462	17.6	440	0.3413	0.5	0.5	0.0	0.5	0.0
0.3541	18.4	460	0.3382	0.5	0.5	0.0	0.5	0.0
0.3579	19.2	480	0.3399	0.5	0.5	0.0	0.5	0.0
0.3466	20.0	500	0.3317	0.5	0.5	0.0	0.5	0.0
0.3314	20.8	520	0.3303	0.5	0.5	0.0	0.5	0.0
0.33	21.6	540	0.3246	0.5	0.5	0.0	0.5	0.0
0.3279	22.4	560	0.3154	0.5	0.5	0.0	0.5	0.0
0.3234	23.2	580	0.3050	0.5	0.5	0.0	0.5	0.0
0.3193	24.0	600	0.2947	0.5	0.5	0.0	0.5	0.0
0.3086	24.8	620	0.2849	0.5013	0.5	0.0013	0.4987	0.0
0.2912	25.6	640	0.2748	0.5013	0.5	0.0013	0.4987	0.0
0.2787	26.4	660	0.2655	0.5107	0.5	0.0107	0.4893	0.0
0.2779	27.2	680	0.2581	0.5177	0.5	0.0177	0.4823	0.0
0.2697	28.0	700	0.2527	0.5170	0.5	0.0170	0.4830	0.0
0.2669	28.8	720	0.2495	0.5259	0.5	0.0259	0.4741	0.0
0.2654	29.6	740	0.2473	0.5278	0.5	0.0278	0.4722	0.0

Framework versions

• Transformers 4.26.1
• Pytorch 1.13.1
• Datasets 2.10.1
• Tokenizers 0.13.2