ASAP_FineTuningBERT_AugV8_k7_task1_organization_k7_fold0

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

• Loss: 0.7037
• Qwk: 0.4599
• Mse: 0.7037
• Rmse: 0.8389

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: 64
• eval_batch_size: 64
• seed: 42
• 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
• num_epochs: 100

Training results

Training Loss	Epoch	Step	Validation Loss	Qwk	Mse	Rmse
No log	1.0	6	6.7894	0.0	6.7894	2.6056
No log	2.0	12	4.2990	0.0039	4.2990	2.0734
No log	3.0	18	2.1171	0.0575	2.1171	1.4550
No log	4.0	24	1.2021	0.0212	1.2021	1.0964
No log	5.0	30	2.5171	0.0940	2.5171	1.5866
No log	6.0	36	1.5371	0.0909	1.5371	1.2398
No log	7.0	42	0.9210	0.2355	0.9210	0.9597
No log	8.0	48	0.8297	0.2535	0.8297	0.9109
No log	9.0	54	0.7071	0.3294	0.7071	0.8409
No log	10.0	60	0.6399	0.4047	0.6399	0.7999
No log	11.0	66	0.6839	0.3913	0.6839	0.8270
No log	12.0	72	0.7010	0.4565	0.7010	0.8372
No log	13.0	78	0.7860	0.4537	0.7860	0.8865
No log	14.0	84	0.7973	0.4307	0.7973	0.8929
No log	15.0	90	0.8911	0.4011	0.8911	0.9440
No log	16.0	96	0.7501	0.4255	0.7501	0.8661
No log	17.0	102	0.7531	0.4640	0.7531	0.8678
No log	18.0	108	0.7039	0.4649	0.7039	0.8390
No log	19.0	114	0.8183	0.4647	0.8183	0.9046
No log	20.0	120	0.7317	0.4374	0.7317	0.8554
No log	21.0	126	0.7943	0.4632	0.7943	0.8913
No log	22.0	132	0.6961	0.4772	0.6961	0.8343
No log	23.0	138	0.8468	0.4318	0.8468	0.9202
No log	24.0	144	0.7956	0.4086	0.7956	0.8919
No log	25.0	150	0.9441	0.3284	0.9441	0.9716
No log	26.0	156	0.7664	0.4699	0.7664	0.8755
No log	27.0	162	0.8578	0.3927	0.8578	0.9262
No log	28.0	168	0.7968	0.4232	0.7968	0.8927
No log	29.0	174	0.7255	0.4636	0.7255	0.8517
No log	30.0	180	0.6727	0.4346	0.6727	0.8202
No log	31.0	186	0.6878	0.4728	0.6878	0.8294
No log	32.0	192	0.7037	0.4599	0.7037	0.8389

Framework versions

• Transformers 4.47.0
• Pytorch 2.5.1+cu121
• Datasets 3.2.0
• Tokenizers 0.21.0