2020-Q2-75p-filtered_combined75

DouglasPontes/2020-Q2-75p-filtered_combined75

2020-Q2-75p-filtered_combined75 is a fill-mask model from DouglasPontes. Use it when you need the model to fill a missing word. It is set up for transformers.

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

Downloads · 30 days

2% of all-time downloads

All-time downloads

170

Public

Repo size

16 GB

Likes

Public

Hugging Face

Repo makeup

Click a slice to open those files.

.bin499 MB · 99%

At a glance

Task: Fill-Mask
Library: transformers
Model type: roberta
Access: Public
Created: Jan 20, 2024
Updated: Jan 25, 2024
SHA: ad25d2f1

Try a prompt

Base models

DouglasPontes/2020-Q1-filtered_tweets

Model card

From the Hugging Face model README

2020-Q2-75p-filtered

This model is a fine-tuned version of DouglasPontes/2020-Q1-filtered_tweets on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 2.2312

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: 4.1e-07
train_batch_size: 16
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.98) and epsilon=1e-08
lr_scheduler_type: linear
training_steps: 2400000

Training results

Training Loss	Epoch	Step	Validation Loss
No log	0.02	8000	2.4865
2.6592	0.04	16000	2.4598
2.6592	0.07	24000	2.4472
2.6211	0.09	32000	2.4341
2.6211	0.11	40000	2.4223
2.6048	0.13	48000	2.4217
2.6048	0.16	56000	2.4184
2.5861	0.18	64000	2.4062
2.5861	0.2	72000	2.3919
2.5736	0.22	80000	2.3896
2.5736	0.25	88000	2.3951
2.5559	0.27	96000	2.3903
2.5559	0.29	104000	2.3836
2.5551	0.31	112000	2.3749
2.5551	0.34	120000	2.3794
2.5371	0.36	128000	2.3733
2.5371	0.38	136000	2.3703
2.5417	0.4	144000	2.3662
2.5417	0.43	152000	2.3728
2.5316	0.45	160000	2.3643
2.5316	0.47	168000	2.3568
2.5296	0.49	176000	2.3555
2.5296	0.52	184000	2.3506
2.5215	0.54	192000	2.3482
2.5215	0.56	200000	2.3514
2.5274	0.58	208000	2.3531
2.5274	0.61	216000	2.3463
2.5215	0.63	224000	2.3470
2.5215	0.65	232000	2.3407
2.5096	0.67	240000	2.3400
2.5096	0.7	248000	2.3402
2.5176	0.72	256000	2.3308
2.5176	0.74	264000	2.3342
2.5048	0.76	272000	2.3333
2.5048	0.79	280000	2.3288
2.4979	0.81	288000	2.3298
2.4979	0.83	296000	2.3237
2.4963	0.85	304000	2.3266
2.4963	0.88	312000	2.3197
2.4972	0.9	320000	2.3271
2.4972	0.92	328000	2.3275
2.4969	0.94	336000	2.3210
2.4969	0.97	344000	2.3222
2.4961	0.99	352000	2.3242
2.4961	1.01	360000	2.3155
2.49	1.03	368000	2.3175
2.49	1.06	376000	2.3076
2.4847	1.08	384000	2.3138
2.4847	1.1	392000	2.3183
2.4767	1.12	400000	2.3118
2.4767	1.15	408000	2.3152
2.4788	1.17	416000	2.3089
2.4788	1.19	424000	2.3051
2.4738	1.21	432000	2.3102
2.4738	1.24	440000	2.3069
2.4635	1.26	448000	2.3004
2.4635	1.28	456000	2.3066
2.4828	1.3	464000	2.3078
2.4828	1.32	472000	2.3072
2.4675	1.35	480000	2.3073
2.4675	1.37	488000	2.3014
2.4676	1.39	496000	2.2987
2.4676	1.41	504000	2.2988
2.4678	1.44	512000	2.2971
2.4678	1.46	520000	2.2969
2.4634	1.48	528000	2.2990
2.4634	1.5	536000	2.2869
2.4657	1.53	544000	2.2936
2.4657	1.55	552000	2.2915
2.4607	1.57	560000	2.2903
2.4607	1.59	568000	2.2934
2.4558	1.62	576000	2.2845
2.4558	1.64	584000	2.2897
2.4662	1.66	592000	2.2928
2.4662	1.68	600000	2.2861
2.4658	1.71	608000	2.2883
2.4658	1.73	616000	2.2878
2.4533	1.75	624000	2.2892
2.4533	1.77	632000	2.2886
2.4575	1.8	640000	2.2894
2.4575	1.82	648000	2.2871
2.4565	1.84	656000	2.2798
2.4565	1.86	664000	2.2877
2.4548	1.89	672000	2.2859
2.4548	1.91	680000	2.2787
2.4507	1.93	688000	2.2780
2.4507	1.95	696000	2.2826
2.4455	1.98	704000	2.2838
2.4455	2.0	712000	2.2764
2.4516	2.02	720000	2.2814
2.4516	2.04	728000	2.2807
2.445	2.07	736000	2.2740
2.445	2.09	744000	2.2780
2.4466	2.11	752000	2.2775
2.4466	2.13	760000	2.2783
2.4476	2.16	768000	2.2763
2.4476	2.18	776000	2.2737
2.4449	2.2	784000	2.2753
2.4449	2.22	792000	2.2762
2.4424	2.25	800000	2.2767
2.4424	2.27	808000	2.2702
2.4528	2.29	816000	2.2655
2.4528	2.31	824000	2.2727
2.4523	2.34	832000	2.2733
2.4523	2.36	840000	2.2654
2.4395	2.38	848000	2.2674
2.4395	2.4	856000	2.2754
2.434	2.43	864000	2.2722
2.434	2.45	872000	2.2666
2.4407	2.47	880000	2.2656
2.4407	2.49	888000	2.2654
2.4352	2.52	896000	2.2630
2.4352	2.54	904000	2.2662
2.4393	2.56	912000	2.2692
2.4393	2.58	920000	2.2558
2.4378	2.61	928000	2.2619
2.4378	2.63	936000	2.2614
2.4392	2.65	944000	2.2578
2.4392	2.67	952000	2.2672
2.437	2.69	960000	2.2598
2.437	2.72	968000	2.2633
2.4388	2.74	976000	2.2566
2.4388	2.76	984000	2.2551
2.4386	2.78	992000	2.2606
2.4386	2.81	1000000	2.2634
2.4402	2.83	1008000	2.2641
2.4402	2.85	1016000	2.2619
2.4442	2.87	1024000	2.2584
2.4442	2.9	1032000	2.2579
2.4327	2.92	1040000	2.2523
2.4327	2.94	1048000	2.2562
2.4289	2.96	1056000	2.2593
2.4289	2.99	1064000	2.2562
2.4319	3.01	1072000	2.2536
2.4319	3.03	1080000	2.2603
2.4174	3.05	1088000	2.2549
2.4174	3.08	1096000	2.2595
2.4155	3.1	1104000	2.2555
2.4155	3.12	1112000	2.2501
2.427	3.14	1120000	2.2528
2.427	3.17	1128000	2.2529
2.4222	3.19	1136000	2.2536
2.4222	3.21	1144000	2.2582
2.4232	3.23	1152000	2.2522
2.4232	3.26	1160000	2.2525
2.4252	3.28	1168000	2.2538
2.4252	3.3	1176000	2.2512
2.4209	3.32	1184000	2.2557
2.4209	3.35	1192000	2.2445
2.4243	3.37	1200000	2.2570
2.4243	3.39	1208000	2.2539
2.4278	3.41	1216000	2.2514
2.4278	3.44	1224000	2.2454
2.4286	3.46	1232000	2.2463
2.4286	3.48	1240000	2.2506
2.4274	3.5	1248000	2.2427
2.4274	3.53	1256000	2.2535
2.4201	3.55	1264000	2.2517
2.4201	3.57	1272000	2.2436
2.4233	3.59	1280000	2.2430
2.4233	3.62	1288000	2.2470
2.4183	3.64	1296000	2.2446
2.4183	3.66	1304000	2.2539
2.428	3.68	1312000	2.2492
2.428	3.71	1320000	2.2544
2.4206	3.73	1328000	2.2478
2.4206	3.75	1336000	2.2420
2.4287	3.77	1344000	2.2442
2.4287	3.8	1352000	2.2426
2.4297	3.82	1360000	2.2426
2.4297	3.84	1368000	2.2481
2.4185	3.86	1376000	2.2449
2.4185	3.89	1384000	2.2468
2.4217	3.91	1392000	2.2467
2.4217	3.93	1400000	2.2463
2.4144	3.95	1408000	2.2482
2.4144	3.97	1416000	2.2424
2.4175	4.0	1424000	2.2415
2.4175	4.02	1432000	2.2451
2.4169	4.04	1440000	2.2443
2.4169	4.06	1448000	2.2389
2.4142	4.09	1456000	2.2377
2.4142	4.11	1464000	2.2399
2.4122	4.13	1472000	2.2447
2.4122	4.15	1480000	2.2456
2.4166	4.18	1488000	2.2451
2.4166	4.2	1496000	2.2369
2.4165	4.22	1504000	2.2426
2.4165	4.24	1512000	2.2384
2.4204	4.27	1520000	2.2454
2.4204	4.29	1528000	2.2422
2.4192	4.31	1536000	2.2423
2.4192	4.33	1544000	2.2435
2.4167	4.36	1552000	2.2451
2.4167	4.38	1560000	2.2443
2.4124	4.4	1568000	2.2430
2.4124	4.42	1576000	2.2422
2.406	4.45	1584000	2.2357
2.406	4.47	1592000	2.2395
2.4166	4.49	1600000	2.2378
2.4166	4.51	1608000	2.2420
2.4144	4.54	1616000	2.2402
2.4144	4.56	1624000	2.2384
2.4219	4.58	1632000	2.2438
2.4219	4.6	1640000	2.2455
2.4061	4.63	1648000	2.2397
2.4061	4.65	1656000	2.2354
2.411	4.67	1664000	2.2393
2.411	4.69	1672000	2.2388
2.4125	4.72	1680000	2.2406
2.4125	4.74	1688000	2.2330
2.4092	4.76	1696000	2.2336
2.4092	4.78	1704000	2.2398
2.4078	4.81	1712000	2.2368
2.4078	4.83	1720000	2.2361
2.4185	4.85	1728000	2.2378
2.4185	4.87	1736000	2.2339
2.4088	4.9	1744000	2.2366
2.4088	4.92	1752000	2.2385
2.4095	4.94	1760000	2.2337
2.4095	4.96	1768000	2.2413
2.4078	4.99	1776000	2.2377
2.4078	5.01	1784000	2.2302
2.4073	5.03	1792000	2.2357
2.4073	5.05	1800000	2.2384
2.4073	5.08	1808000	2.2322
2.4073	5.1	1816000	2.2344
2.4043	5.12	1824000	2.2327
2.4043	5.14	1832000	2.2350
2.4082	5.17	1840000	2.2376
2.4082	5.19	1848000	2.2363
2.4073	5.21	1856000	2.2323
2.4073	5.23	1864000	2.2419
2.4148	5.26	1872000	2.2293
2.4148	5.28	1880000	2.2346
2.4098	5.3	1888000	2.2372
2.4098	5.32	1896000	2.2371
2.407	5.34	1904000	2.2397
2.407	5.37	1912000	2.2300
2.4108	5.39	1920000	2.2317
2.4108	5.41	1928000	2.2350
2.4168	5.43	1936000	2.2343
2.4168	5.46	1944000	2.2327
2.4113	5.48	1952000	2.2363
2.4113	5.5	1960000	2.2314
2.4131	5.52	1968000	2.2303
2.4131	5.55	1976000	2.2353
2.4129	5.57	1984000	2.2353
2.4129	5.59	1992000	2.2296
2.4129	5.61	2000000	2.2314
2.4129	5.64	2008000	2.2288
2.4045	5.66	2016000	2.2347
2.4045	5.68	2024000	2.2349
2.4089	5.7	2032000	2.2310
2.4089	5.73	2040000	2.2342
2.4091	5.75	2048000	2.2320
2.4091	5.77	2056000	2.2311
2.4137	5.79	2064000	2.2278
2.4137	5.82	2072000	2.2344
2.4063	5.84	2080000	2.2339
2.4063	5.86	2088000	2.2271
2.4046	5.88	2096000	2.2263
2.4046	5.91	2104000	2.2369
2.4105	5.93	2112000	2.2330
2.4105	5.95	2120000	2.2361
2.4045	5.97	2128000	2.2320
2.4045	6.0	2136000	2.2283
2.4093	6.02	2144000	2.2262
2.4093	6.04	2152000	2.2294
2.4109	6.06	2160000	2.2334
2.4109	6.09	2168000	2.2363
2.4061	6.11	2176000	2.2309
2.4061	6.13	2184000	2.2269
2.4007	6.15	2192000	2.2369
2.4007	6.18	2200000	2.2297
2.4034	6.2	2208000	2.2267
2.4034	6.22	2216000	2.2310
2.4049	6.24	2224000	2.2362
2.4049	6.27	2232000	2.2319
2.4052	6.29	2240000	2.2308
2.4052	6.31	2248000	2.2225
2.4102	6.33	2256000	2.2366
2.4102	6.36	2264000	2.2327
2.4046	6.38	2272000	2.2305
2.4046	6.4	2280000	2.2309
2.4066	6.42	2288000	2.2291
2.4066	6.45	2296000	2.2301
2.4041	6.47	2304000	2.2378
2.4041	6.49	2312000	2.2317
2.4081	6.51	2320000	2.2326
2.4081	6.54	2328000	2.2412
2.4147	6.56	2336000	2.2349
2.4147	6.58	2344000	2.2296
2.4105	6.6	2352000	2.2313
2.4105	6.62	2360000	2.2297
2.4096	6.65	2368000	2.2241
2.4096	6.67	2376000	2.2322
2.4089	6.69	2384000	2.2344
2.4089	6.71	2392000	2.2291
2.4048	6.74	2400000	2.2274

Framework versions

Transformers 4.35.0.dev0
Pytorch 2.0.1+cu117
Datasets 2.14.5
Tokenizers 0.14.0

Task: Fill-Mask
Library: transformers
Type: roberta
Created: Jan 20, 2024
Updated: Jan 25, 2024