auto_bot

Bhaveshgb/auto_bot

auto_bot is a question answering model from Bhaveshgb. Use it when the input is a question plus a passage. It is set up for transformers. The card lists the license as mit.

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

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Hugging Face

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At a glance

Task: Question Answering
Library: transformers
License: mit
Model type: electra
Access: Public
Created: Feb 13, 2023
Updated: Feb 13, 2023
SHA: 5b6db373

Try a prompt

Model card

From the Hugging Face model README

auto_bot

This model is a fine-tuned version of deepset/gelectra-base-germanquad on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 3.1041

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: 16
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 100

Training results

Training Loss	Epoch	Step	Validation Loss
No log	1.0	1	2.7932
No log	2.0	2	2.8536
No log	3.0	3	2.8856
No log	4.0	4	2.9470
No log	5.0	5	2.9948
No log	6.0	6	3.0745
No log	7.0	7	3.1467
No log	8.0	8	3.2018
No log	9.0	9	3.2549
No log	10.0	10	3.2827
No log	11.0	11	3.2572
No log	12.0	12	3.1982
No log	13.0	13	3.1229
No log	14.0	14	3.0666
No log	15.0	15	3.0209
No log	16.0	16	2.9706
No log	17.0	17	2.9060
No log	18.0	18	2.8304
No log	19.0	19	2.7950
No log	20.0	20	2.7435
No log	21.0	21	2.7194
No log	22.0	22	2.7012
No log	23.0	23	2.6803
No log	24.0	24	2.6647
No log	25.0	25	2.6490
No log	26.0	26	2.6476
No log	27.0	27	2.6626
No log	28.0	28	2.6928
No log	29.0	29	2.7398
No log	30.0	30	2.7371
No log	31.0	31	2.7501
No log	32.0	32	2.7698
No log	33.0	33	2.7965
No log	34.0	34	2.8332
No log	35.0	35	2.8756
No log	36.0	36	2.9246
No log	37.0	37	2.9754
No log	38.0	38	3.0306
No log	39.0	39	3.0738
No log	40.0	40	3.1037
No log	41.0	41	3.1197
No log	42.0	42	3.1269
No log	43.0	43	3.1520
No log	44.0	44	3.1566
No log	45.0	45	3.1706
No log	46.0	46	3.1815
No log	47.0	47	3.1709
No log	48.0	48	3.1615
No log	49.0	49	3.1367
No log	50.0	50	3.1303
No log	51.0	51	3.1252
No log	52.0	52	3.1182
No log	53.0	53	3.1105
No log	54.0	54	3.0899
No log	55.0	55	3.0767
No log	56.0	56	3.0598
No log	57.0	57	3.0419
No log	58.0	58	3.0298
No log	59.0	59	3.0371
No log	60.0	60	3.0315
No log	61.0	61	3.0238
No log	62.0	62	3.0137
No log	63.0	63	3.0129
No log	64.0	64	3.0188
No log	65.0	65	3.0242
No log	66.0	66	3.0289
No log	67.0	67	3.0293
No log	68.0	68	3.0229
No log	69.0	69	3.0187
No log	70.0	70	3.0121
No log	71.0	71	3.0028
No log	72.0	72	2.9944
No log	73.0	73	2.9858
No log	74.0	74	2.9779
No log	75.0	75	2.9792
No log	76.0	76	2.9778
No log	77.0	77	2.9800
No log	78.0	78	2.9846
No log	79.0	79	2.9932
No log	80.0	80	3.0056
No log	81.0	81	3.0129
No log	82.0	82	3.0216
No log	83.0	83	3.0312
No log	84.0	84	3.0401
No log	85.0	85	3.0507
No log	86.0	86	3.0582
No log	87.0	87	3.0625
No log	88.0	88	3.0660
No log	89.0	89	3.0694
No log	90.0	90	3.0757
No log	91.0	91	3.0818
No log	92.0	92	3.0873
No log	93.0	93	3.0904
No log	94.0	94	3.0936
No log	95.0	95	3.0975
No log	96.0	96	3.1001
No log	97.0	97	3.1019
No log	98.0	98	3.1030
No log	99.0	99	3.1038
No log	100.0	100	3.1041

Framework versions

Transformers 4.26.1
Pytorch 1.13.1
Datasets 2.9.0
Tokenizers 0.13.2

Task: Question Answering
Library: transformers
Type: electra
License: mit
Created: Feb 13, 2023
Updated: Feb 13, 2023