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Pstman/my_text_gen_model

sourceHugging Faceapache-2.0updated 3y agoView on Hugging Face

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mytextgen_model

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

—Loss: 0.0000
—Rouge1: 0.395
—Rouge2: 0.376
—Rougel: 0.3954
—Rougelsum: 0.3949
—Gen Len: 18.0

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: 2e-05
—trainbatchsize: 4
—evalbatchsize: 4
—seed: 42
—optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
—lrschedulertype: linear
—num_epochs: 100

Training results

Training Loss	Epoch	Step	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
No log	1.0	202	0.395	0.376	0.3954	0.3949	18.0
No log	2.0	404	0.395	0.376	0.3954	0.3949	18.0
0.008	3.0	606	0.395	0.376	0.3954	0.3949	18.0
0.008	4.0	808	0.395	0.376	0.3954	0.3949	18.0
0.0042	5.0	1010	0.395	0.376	0.3954	0.3949	18.0
0.0042	6.0	1212	0.395	0.376	0.3954	0.3949	18.0
0.0042	7.0	1414	0.395	0.376	0.3954	0.3949	18.0
0.0022	8.0	1616	0.395	0.376	0.3954	0.3949	18.0
0.0022	9.0	1818	0.395	0.376	0.3954	0.3949	18.0
0.004	10.0	2020	0.395	0.376	0.3954	0.3949	18.0
0.004	11.0	2222	0.395	0.376	0.3954	0.3949	18.0
0.004	12.0	2424	0.395	0.376	0.3954	0.3949	18.0
0.0025	13.0	2626	0.395	0.376	0.3954	0.3949	18.0
0.0025	14.0	2828	0.395	0.376	0.3954	0.3949	18.0
0.0016	15.0	3030	0.395	0.376	0.3954	0.3949	18.0
0.0016	16.0	3232	0.395	0.376	0.3954	0.3949	18.0
0.0016	17.0	3434	0.395	0.376	0.3954	0.3949	18.0
0.0019	18.0	3636	0.395	0.376	0.3954	0.3949	18.0
0.0019	19.0	3838	0.395	0.376	0.3954	0.3949	18.0
0.0019	20.0	4040	0.395	0.376	0.3954	0.3949	18.0
0.0019	21.0	4242	0.395	0.376	0.3954	0.3949	18.0
0.0019	22.0	4444	0.395	0.376	0.3954	0.3949	18.0
0.0012	23.0	4646	0.395	0.376	0.3954	0.3949	18.0
0.0012	24.0	4848	0.395	0.376	0.3954	0.3949	18.0
0.0013	25.0	5050	0.395	0.376	0.3954	0.3949	18.0
0.0013	26.0	5252	0.395	0.376	0.3954	0.3949	18.0
0.0013	27.0	5454	0.395	0.376	0.3954	0.3949	18.0
0.0012	28.0	5656	0.395	0.376	0.3954	0.3949	18.0
0.0012	29.0	5858	0.395	0.376	0.3954	0.3949	18.0
0.0015	30.0	6060	0.395	0.376	0.3954	0.3949	18.0
0.0015	31.0	6262	0.395	0.376	0.3954	0.3949	18.0
0.0015	32.0	6464	0.395	0.376	0.3954	0.3949	18.0
0.0011	33.0	6666	0.395	0.376	0.3954	0.3949	18.0
0.0011	34.0	6868	0.395	0.376	0.3954	0.3949	18.0
0.0011	35.0	7070	0.395	0.376	0.3954	0.3949	18.0
0.0011	36.0	7272	0.395	0.376	0.3954	0.3949	18.0
0.0011	37.0	7474	0.395	0.376	0.3954	0.3949	18.0
0.0011	38.0	7676	0.395	0.376	0.3954	0.3949	18.0
0.0011	39.0	7878	0.395	0.376	0.3954	0.3949	18.0
0.0009	40.0	8080	0.395	0.376	0.3954	0.3949	18.0
0.0009	41.0	8282	0.395	0.376	0.3954	0.3949	18.0
0.0009	42.0	8484	0.395	0.376	0.3954	0.3949	18.0
0.0004	43.0	8686	0.395	0.376	0.3954	0.3949	18.0
0.0004	44.0	8888	0.395	0.376	0.3954	0.3949	18.0
0.0006	45.0	9090	0.395	0.376	0.3954	0.3949	18.0
0.0006	46.0	9292	0.395	0.376	0.3954	0.3949	18.0
0.0006	47.0	9494	0.395	0.376	0.3954	0.3949	18.0
0.0007	48.0	9696	0.395	0.376	0.3954	0.3949	18.0
0.0007	49.0	9898	0.395	0.376	0.3954	0.3949	18.0
0.0008	50.0	10100	0.395	0.376	0.3954	0.3949	18.0
0.0008	51.0	10302	0.395	0.376	0.3954	0.3949	18.0
0.0003	52.0	10504	0.395	0.376	0.3954	0.3949	18.0
0.0003	53.0	10706	0.395	0.376	0.3954	0.3949	18.0
0.0003	54.0	10908	0.395	0.376	0.3954	0.3949	18.0
0.0003	55.0	11110	0.395	0.376	0.3954	0.3949	18.0
0.0003	56.0	11312	0.395	0.376	0.3954	0.3949	18.0
0.0005	57.0	11514	0.395	0.376	0.3954	0.3949	18.0
0.0005	58.0	11716	0.395	0.376	0.3954	0.3949	18.0
0.0005	59.0	11918	0.395	0.376	0.3954	0.3949	18.0
0.0015	60.0	12120	0.395	0.376	0.3954	0.3949	18.0
0.0015	61.0	12322	0.395	0.376	0.3954	0.3949	18.0
0.0005	62.0	12524	0.395	0.376	0.3954	0.3949	18.0
0.0005	63.0	12726	0.395	0.376	0.3954	0.3949	18.0
0.0005	64.0	12928	0.395	0.376	0.3954	0.3949	18.0
0.0013	65.0	13130	0.395	0.376	0.3954	0.3949	18.0
0.0013	66.0	13332	0.395	0.376	0.3954	0.3949	18.0
0.0002	67.0	13534	0.395	0.376	0.3954	0.3949	18.0
0.0002	68.0	13736	0.395	0.376	0.3954	0.3949	18.0
0.0002	69.0	13938	0.395	0.376	0.3954	0.3949	18.0
0.0001	70.0	14140	0.395	0.376	0.3954	0.3949	18.0
0.0001	71.0	14342	0.395	0.376	0.3954	0.3949	18.0
0.0005	72.0	14544	0.395	0.376	0.3954	0.3949	18.0
0.0005	73.0	14746	0.395	0.376	0.3954	0.3949	18.0
0.0005	74.0	14948	0.395	0.376	0.3954	0.3949	18.0
0.0005	75.0	15150	0.395	0.376	0.3954	0.3949	18.0
0.0005	76.0	15352	0.395	0.376	0.3954	0.3949	18.0
0.0004	77.0	15554	0.395	0.376	0.3954	0.3949	18.0
0.0004	78.0	15756	0.395	0.376	0.3954	0.3949	18.0
0.0004	79.0	15958	0.395	0.376	0.3954	0.3949	18.0
0.0004	80.0	16160	0.395	0.376	0.3954	0.3949	18.0
0.0004	81.0	16362	0.395	0.376	0.3954	0.3949	18.0
0.0002	82.0	16564	0.395	0.376	0.3954	0.3949	18.0
0.0002	83.0	16766	0.395	0.376	0.3954	0.3949	18.0
0.0002	84.0	16968	0.395	0.376	0.3954	0.3949	18.0
0.0005	85.0	17170	0.395	0.376	0.3954	0.3949	18.0
0.0005	86.0	17372	0.395	0.376	0.3954	0.3949	18.0
0.0003	87.0	17574	0.395	0.376	0.3954	0.3949	18.0
0.0003	88.0	17776	0.395	0.376	0.3954	0.3949	18.0
0.0003	89.0	17978	0.395	0.376	0.3954	0.3949	18.0
0.0002	90.0	18180	0.395	0.376	0.3954	0.3949	18.0
0.0002	91.0	18382	0.395	0.376	0.3954	0.3949	18.0
0.0001	92.0	18584	0.395	0.376	0.3954	0.3949	18.0
0.0001	93.0	18786	0.395	0.376	0.3954	0.3949	18.0
0.0001	94.0	18988	0.395	0.376	0.3954	0.3949	18.0
0.0003	95.0	19190	0.395	0.376	0.3954	0.3949	18.0
0.0003	96.0	19392	0.395	0.376	0.3954	0.3949	18.0
0.0	97.0	19594	0.395	0.376	0.3954	0.3949	18.0
0.0	98.0	19796	0.395	0.376	0.3954	0.3949	18.0
0.0	99.0	19998	0.395	0.376	0.3954	0.3949	18.0
0.0001	100.0	20200	0.395	0.376	0.3954	0.3949	18.0

Framework versions

—Transformers 4.30.0
—Pytorch 2.0.1+cu118
—Datasets 2.12.0
—Tokenizers 0.13.3