Training in progress, epoch 9

model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:aa435b5d5128cb42a840438c5750299de3b5d75b06e70f57f6d654e4cc806af7
+oid sha256:2cd4adbdf1271f2a1c4a482089d1bd932900fb6be36de92145b11f9266323133
 size 496244100

tb/events.out.tfevents.1725884095.0a1c9bec2a53.15221.0

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:d97e4ea47d55e0442c38ef1175ed7592311ea7f17158677f26d013f6263b1a38
-size 9371
+oid sha256:89d448c7000393aa4739bd3e8685df3e41ddb26d68381c46149f020f68e8f6eb
+size 10054

train.log

@@ -750,4 +750,61 @@ You should probably TRAIN this model on a down-stream task to be able to use it
 [INFO|tokenization_utils_base.py:2693] 2024-09-09 12:26:49,103 >> Special tokens file saved in /content/dissertation/scripts/ner/output/checkpoint-1368/special_tokens_map.json
 [INFO|tokenization_utils_base.py:2684] 2024-09-09 12:26:52,194 >> tokenizer config file saved in /content/dissertation/scripts/ner/output/tokenizer_config.json
 [INFO|tokenization_utils_base.py:2693] 2024-09-09 12:26:52,195 >> Special tokens file saved in /content/dissertation/scripts/ner/output/special_tokens_map.json
-
 80%|████████  | 1369/1710 [11:56<19:51,  3.49s/it]
 80%|████████  | 1370/1710 [11:57<14:28,  2.56s/it]
 80%|████████  | 1371/1710 [11:57<11:06,  1.97s/it]
 80%|████████  | 1372/1710 [11:58<08:31,  1.51s/it]
 80%|████████  | 1373/1710 [11:59<07:28,  1.33s/it]
 80%|████████  | 1374/1710 [11:59<05:54,  1.06s/it]
 80%|████████  | 1375/1710 [12:00<04:53,  1.14it/s]
 80%|████████  | 1376/1710 [12:00<04:04,  1.37it/s]
 81%|████████  | 1377/1710 [12:00<03:26,  1.61it/s]
 81%|████████  | 1378/1710 [12:01<02:59,  1.85it/s]
 81%|████████  | 1379/1710 [12:01<02:45,  2.00it/s]
 81%|████████  | 1380/1710 [12:02<02:33,  2.15it/s]
 81%|████████  | 1381/1710 [12:02<02:32,  2.16it/s]
 81%|████████  | 1382/1710 [12:03<02:40,  2.05it/s]
 81%|████████  | 1383/1710 [12:03<02:37,  2.08it/s]
 81%|████████  | 1384/1710 [12:04<02:38,  2.06it/s]
 81%|████████  | 1385/1710 [12:04<02:31,  2.14it/s]
 81%|████████  | 1386/1710 [12:04<02:37,  2.06it/s]
 81%|████████  | 1387/1710 [12:05<02:28,  2.18it/s]
 81%|████████  | 1388/1710 [12:05<02:26,  2.20it/s]
 81%|████████  | 1389/1710 [12:06<02:26,  2.19it/s]
 81%|████████▏ | 1390/1710 [12:06<02:17,  2.32it/s]
 81%|████████▏ | 1391/1710 [12:07<02:20,  2.27it/s]
 81%|████████▏ | 1392/1710 [12:07<02:18,  2.30it/s]
 81%|████████▏ | 1393/1710 [12:07<02:16,  2.32it/s]
 82%|████████▏ | 1394/1710 [12:08<02:18,  2.28it/s]
 82%|████████▏ | 1395/1710 [12:08<02:13,  2.36it/s]
 82%|████████▏ | 1396/1710 [12:09<02:16,  2.29it/s]
 82%|████████▏ | 1397/1710 [12:09<02:42,  1.93it/s]
 82%|████████▏ | 1398/1710 [12:10<02:31,  2.06it/s]
 82%|████████▏ | 1399/1710 [12:11<02:50,  1.82it/s]
 82%|████████▏ | 1400/1710 [12:11<02:38,  1.96it/s]
 82%|████████▏ | 1401/1710 [12:11<02:22,  2.16it/s]
 82%|████████▏ | 1402/1710 [12:12<02:24,  2.13it/s]
 82%|████████▏ | 1403/1710 [12:12<02:20,  2.18it/s]
 82%|████████▏ | 1404/1710 [12:13<02:21,  2.16it/s]
 82%|████████▏ | 1405/1710 [12:13<02:30,  2.03it/s]
 82%|████████▏ | 1406/1710 [12:14<02:24,  2.10it/s]
 82%|████████▏ | 1407/1710 [12:15<02:52,  1.76it/s]
 82%|████████▏ | 1408/1710 [12:16<03:35,  1.40it/s]
 82%|████████▏ | 1409/1710 [12:16<03:47,  1.32it/s]
 82%|████████▏ | 1410/1710 [12:17<03:23,  1.48it/s]
 83%|████████▎ | 1411/1710 [12:17<02:55,  1.71it/s]
 83%|████████▎ | 1412/1710 [12:18<02:33,  1.94it/s]
 83%|████████▎ | 1413/1710 [12:18<02:23,  2.08it/s]
 83%|████████▎ | 1414/1710 [12:18<02:17,  2.16it/s]
 83%|████████▎ | 1415/1710 [12:19<02:15,  2.17it/s]
 83%|████████▎ | 1416/1710 [12:19<02:07,  2.30it/s]
 83%|████████▎ | 1417/1710 [12:20<01:57,  2.49it/s]
 83%|████████▎ | 1418/1710 [12:20<01:58,  2.46it/s]
 83%|████████▎ | 1419/1710 [12:20<01:54,  2.54it/s]
 83%|████████▎ | 1420/1710 [12:21<02:08,  2.26it/s]
 83%|████████▎ | 1421/1710 [12:21<02:10,  2.21it/s]
 83%|████████▎ | 1422/1710 [12:22<02:06,  2.27it/s]
 83%|████████▎ | 1423/1710 [12:22<01:59,  2.41it/s]
 83%|████████▎ | 1424/1710 [12:23<02:01,  2.36it/s]
 83%|████████▎ | 1425/1710 [12:23<01:57,  2.43it/s]
 83%|████████▎ | 1426/1710 [12:24<02:04,  2.29it/s]
 83%|████████▎ | 1427/1710 [12:24<02:07,  2.23it/s]
 84%|████████▎ | 1428/1710 [12:24<01:56,  2.42it/s]
 84%|████████▎ | 1429/1710 [12:25<02:06,  2.23it/s]
 84%|████████▎ | 1430/1710 [12:25<02:16,  2.05it/s]
 84%|████████▎ | 1431/1710 [12:26<02:13,  2.10it/s]
 84%|████████▎ | 1432/1710 [12:26<02:07,  2.18it/s]
 84%|████████▍ | 1433/1710 [12:27<01:57,  2.35it/s]
 84%|█��██████▍ | 1434/1710 [12:27<02:11,  2.10it/s]
 84%|████████▍ | 1435/1710 [12:28<02:07,  2.16it/s]
 84%|████████▍ | 1436/1710 [12:28<02:02,  2.24it/s]
 84%|████████▍ | 1437/1710 [12:28<01:56,  2.35it/s]
 84%|████████▍ | 1438/1710 [12:29<01:52,  2.43it/s]
 84%|████████▍ | 1439/1710 [12:29<01:56,  2.33it/s]
 84%|████████▍ | 1440/1710 [12:30<02:07,  2.11it/s]
 84%|████████▍ | 1441/1710 [12:30<02:08,  2.09it/s]
 84%|████████▍ | 1442/1710 [12:31<02:10,  2.06it/s]
+
 80%|████████  | 1369/1710 [11:56<19:51,  3.49s/it]
 80%|████████  | 1370/1710 [11:57<14:28,  2.56s/it]
 80%|████████  | 1371/1710 [11:57<11:06,  1.97s/it]
 80%|████████  | 1372/1710 [11:58<08:31,  1.51s/it]
 80%|████████  | 1373/1710 [11:59<07:28,  1.33s/it]
 80%|████████  | 1374/1710 [11:59<05:54,  1.06s/it]
 80%|████████  | 1375/1710 [12:00<04:53,  1.14it/s]
 80%|████████  | 1376/1710 [12:00<04:04,  1.37it/s]
 81%|████████  | 1377/1710 [12:00<03:26,  1.61it/s]
 81%|████████  | 1378/1710 [12:01<02:59,  1.85it/s]
 81%|████████  | 1379/1710 [12:01<02:45,  2.00it/s]
 81%|████████  | 1380/1710 [12:02<02:33,  2.15it/s]
 81%|████████  | 1381/1710 [12:02<02:32,  2.16it/s]
 81%|████████  | 1382/1710 [12:03<02:40,  2.05it/s]
 81%|████████  | 1383/1710 [12:03<02:37,  2.08it/s]
 81%|████████  | 1384/1710 [12:04<02:38,  2.06it/s]
 81%|████████  | 1385/1710 [12:04<02:31,  2.14it/s]
 81%|████████  | 1386/1710 [12:04<02:37,  2.06it/s]
 81%|████████  | 1387/1710 [12:05<02:28,  2.18it/s]
 81%|████████  | 1388/1710 [12:05<02:26,  2.20it/s]
 81%|████████  | 1389/1710 [12:06<02:26,  2.19it/s]
 81%|████████▏ | 1390/1710 [12:06<02:17,  2.32it/s]
 81%|████████▏ | 1391/1710 [12:07<02:20,  2.27it/s]
 81%|████████▏ | 1392/1710 [12:07<02:18,  2.30it/s]
 81%|████████▏ | 1393/1710 [12:07<02:16,  2.32it/s]
 82%|████████▏ | 1394/1710 [12:08<02:18,  2.28it/s]
 82%|████████▏ | 1395/1710 [12:08<02:13,  2.36it/s]
 82%|████████▏ | 1396/1710 [12:09<02:16,  2.29it/s]
 82%|████████▏ | 1397/1710 [12:09<02:42,  1.93it/s]
 82%|████████▏ | 1398/1710 [12:10<02:31,  2.06it/s]
 82%|████████▏ | 1399/1710 [12:11<02:50,  1.82it/s]
 82%|████████▏ | 1400/1710 [12:11<02:38,  1.96it/s]
 82%|████████▏ | 1401/1710 [12:11<02:22,  2.16it/s]
 82%|████████▏ | 1402/1710 [12:12<02:24,  2.13it/s]
 82%|████████▏ | 1403/1710 [12:12<02:20,  2.18it/s]
 82%|████████▏ | 1404/1710 [12:13<02:21,  2.16it/s]
 82%|████████▏ | 1405/1710 [12:13<02:30,  2.03it/s]
 82%|████████▏ | 1406/1710 [12:14<02:24,  2.10it/s]
 82%|████████▏ | 1407/1710 [12:15<02:52,  1.76it/s]
 82%|████████▏ | 1408/1710 [12:16<03:35,  1.40it/s]
 82%|████████▏ | 1409/1710 [12:16<03:47,  1.32it/s]
 82%|████████▏ | 1410/1710 [12:17<03:23,  1.48it/s]
 83%|████████▎ | 1411/1710 [12:17<02:55,  1.71it/s]
 83%|████████▎ | 1412/1710 [12:18<02:33,  1.94it/s]
 83%|████████▎ | 1413/1710 [12:18<02:23,  2.08it/s]
 83%|████████▎ | 1414/1710 [12:18<02:17,  2.16it/s]
 83%|████████▎ | 1415/1710 [12:19<02:15,  2.17it/s]
 83%|████████▎ | 1416/1710 [12:19<02:07,  2.30it/s]
 83%|████████▎ | 1417/1710 [12:20<01:57,  2.49it/s]
 83%|████████▎ | 1418/1710 [12:20<01:58,  2.46it/s]
 83%|████████▎ | 1419/1710 [12:20<01:54,  2.54it/s]
 83%|████████▎ | 1420/1710 [12:21<02:08,  2.26it/s]
 83%|████████▎ | 1421/1710 [12:21<02:10,  2.21it/s]
 83%|████████▎ | 1422/1710 [12:22<02:06,  2.27it/s]
 83%|████████▎ | 1423/1710 [12:22<01:59,  2.41it/s]
 83%|████████▎ | 1424/1710 [12:23<02:01,  2.36it/s]
 83%|████████▎ | 1425/1710 [12:23<01:57,  2.43it/s]
 83%|████████▎ | 1426/1710 [12:24<02:04,  2.29it/s]
 83%|████████▎ | 1427/1710 [12:24<02:07,  2.23it/s]
 84%|████████▎ | 1428/1710 [12:24<01:56,  2.42it/s]
 84%|████████▎ | 1429/1710 [12:25<02:06,  2.23it/s]
 84%|████████▎ | 1430/1710 [12:25<02:16,  2.05it/s]
 84%|████████▎ | 1431/1710 [12:26<02:13,  2.10it/s]
 84%|████████▎ | 1432/1710 [12:26<02:07,  2.18it/s]
 84%|████████▍ | 1433/1710 [12:27<01:57,  2.35it/s]
 84%|████████▍ | 1434/1710 [12:27<02:11,  2.10it/s]
 84%|████████▍ | 1435/1710 [12:28<02:07,  2.16it/s]
 84%|████████▍ | 1436/1710 [12:28<02:02,  2.24it/s]
 84%|████████▍ | 1437/1710 [12:28<01:56,  2.35it/s]
 84%|████████▍ | 1438/1710 [12:29<01:52,  2.43it/s]
 84%|████████▍ | 1439/1710 [12:29<01:56,  2.33it/s]
 84%|████████▍ | 1440/1710 [12:30<02:07,  2.11it/s]
 84%|████████▍ | 1441/1710 [12:30<02:08,  2.09it/s]
 84%|████████▍ | 1442/1710 [12:31<02:10,  2.06it/s]
 84%|████████▍ | 1443/1710 [12:31<02:04,  2.15it/s]
 84%|████████▍ | 1444/1710 [12:32<01:54,  2.31it/s]
 85%|████████▍ | 1445/1710 [12:32<01:48,  2.45it/s]
 85%|████████▍ | 1446/1710 [12:33<01:57,  2.24it/s]
 85%|████████▍ | 1447/1710 [12:33<01:56,  2.25it/s]
 85%|████████▍ | 1448/1710 [12:33<01:47,  2.44it/s]
 85%|████████▍ | 1449/1710 [12:34<01:46,  2.46it/s]
 85%|████████▍ | 1450/1710 [12:34<01:52,  2.31it/s]
 85%|████████▍ | 1451/1710 [12:35<02:04,  2.09it/s]
 85%|████████▍ | 1452/1710 [12:35<02:05,  2.06it/s]
 85%|████████▍ | 1453/1710 [12:36<02:00,  2.12it/s]
 85%|████████▌ | 1454/1710 [12:36<01:53,  2.26it/s]
 85%|████████▌ | 1455/1710 [12:37<01:51,  2.28it/s]
 85%|████████▌ | 1456/1710 [12:37<01:45,  2.41it/s]
 85%|████████▌ | 1457/1710 [12:37<01:47,  2.36it/s]
 85%|████████▌ | 1458/1710 [12:38<01:44,  2.41it/s]
 85%|████████▌ | 1459/1710 [12:38<01:47,  2.33it/s]
 85%|████████▌ | 1460/1710 [12:39<01:46,  2.34it/s]
 85%|████████▌ | 1461/1710 [12:39<01:53,  2.19it/s]
 85%|████████▌ | 1462/1710 [12:40<02:08,  1.94it/s]
 86%|████████▌ | 1463/1710 [12:40<01:57,  2.10it/s]
 86%|████████▌ | 1464/1710 [12:41<01:51,  2.21it/s]
 86%|████████▌ | 1465/1710 [12:41<01:52,  2.18it/s]
 86%|████████▌ | 1466/1710 [12:41<01:46,  2.28it/s]
 86%|████████▌ | 1467/1710 [12:42<01:45,  2.30it/s]
 86%|████████▌ | 1468/1710 [12:42<01:41,  2.38it/s]
 86%|████████▌ | 1469/1710 [12:43<01:59,  2.02it/s]
 86%|████████▌ | 1470/1710 [12:44<02:15,  1.77it/s]
 86%|████████▌ | 1471/1710 [12:44<02:11,  1.82it/s]
 86%|████████▌ | 1472/1710 [12:45<02:07,  1.86it/s]
 86%|████████▌ | 1473/1710 [12:45<02:00,  1.96it/s]
 86%|████████▌ | 1474/1710 [12:46<01:53,  2.09it/s]
 86%|████████▋ | 1475/1710 [12:46<01:43,  2.28it/s]
 86%|████████▋ | 1476/1710 [12:46<01:42,  2.29it/s]
 86%|████████▋ | 1477/1710 [12:47<01:37,  2.38it/s]
 86%|████████▋ | 1478/1710 [12:47<01:37,  2.38it/s]
 86%|████████▋ | 1479/1710 [12:48<01:39,  2.32it/s]
 87%|████████▋ | 1480/1710 [12:48<01:39,  2.30it/s]
 87%|████████▋ | 1481/1710 [12:49<01:56,  1.97it/s]
 87%|████████▋ | 1482/1710 [12:49<01:47,  2.12it/s]
 87%|████████▋ | 1483/1710 [12:50<01:46,  2.13it/s]
 87%|████████▋ | 1484/1710 [12:50<01:42,  2.21it/s]
 87%|████████▋ | 1485/1710 [12:51<01:58,  1.89it/s]
 87%|████████▋ | 1486/1710 [12:51<01:48,  2.07it/s]
 87%|████████▋ | 1487/1710 [12:52<01:54,  1.96it/s]
 87%|████████▋ | 1488/1710 [12:52<01:42,  2.16it/s]
 87%|████████▋ | 1489/1710 [12:52<01:37,  2.28it/s]
 87%|████████▋ | 1490/1710 [12:53<02:03,  1.79it/s]
 87%|████████▋ | 1491/1710 [12:54<01:48,  2.02it/s]
 87%|████████▋ | 1492/1710 [12:54<01:42,  2.13it/s]
 87%|████████▋ | 1493/1710 [12:54<01:40,  2.15it/s]
 87%|████████▋ | 1494/1710 [12:55<01:41,  2.13it/s]
 87%|████████▋ | 1495/1710 [12:55<01:38,  2.19it/s]
 87%|████████▋ | 1496/1710 [12:56<01:30,  2.37it/s]
 88%|████████▊ | 1497/1710 [12:56<01:30,  2.35it/s]
 88%|████████▊ | 1498/1710 [12:57<01:30,  2.35it/s]
 88%|████████▊ | 1499/1710 [12:57<01:59,  1.77it/s]
 88%|████████▊ | 1500/1710 [12:58<01:50,  1.90it/s]
                                                   
 88%|████████▊ | 1500/1710 [12:58<01:50,  1.90it/s]
 88%|████████▊ | 1501/1710 [12:58<01:48,  1.92it/s]
 88%|████████▊ | 1502/1710 [12:59<01:37,  2.13it/s]
 88%|████████▊ | 1503/1710 [12:59<01:27,  2.37it/s]
 88%|████████▊ | 1504/1710 [13:00<01:32,  2.24it/s]
 88%|████████▊ | 1505/1710 [13:00<01:29,  2.29it/s]
 88%|████████▊ | 1506/1710 [13:01<01:37,  2.09it/s]
 88%|████████▊ | 1507/1710 [13:01<01:32,  2.20it/s]
 88%|████████▊ | 1508/1710 [13:01<01:24,  2.39it/s]
 88%|████████▊ | 1509/1710 [13:02<01:18,  2.57it/s]
 88%|████████▊ | 1510/1710 [13:02<01:15,  2.64it/s]
 88%|████████▊ | 1511/1710 [13:02<01:17,  2.58it/s]
 88%|████████▊ | 1512/1710 [13:03<01:26,  2.29it/s]
 88%|████████▊ | 1513/1710 [13:03<01:29,  2.21it/s]
 89%|████████▊ | 1514/1710 [13:04<01:20,  2.43it/s]
 89%|████████▊ | 1515/1710 [13:04<01:19,  2.47it/s]
 89%|████████▊ | 1516/1710 [13:05<01:24,  2.30it/s]
 89%|████████▊ | 1517/1710 [13:05<01:21,  2.37it/s]
 89%|████████▉ | 1518/1710 [13:05<01:20,  2.40it/s]
 89%|████████▉ | 1519/1710 [13:06<01:20,  2.36it/s]
 89%|████████▉ | 1520/1710 [13:06<01:17,  2.46it/s]
 89%|████████▉ | 1521/1710 [13:07<01:28,  2.13it/s]
 89%|████████▉ | 1522/1710 [13:07<01:33,  2.01it/s]
 89%|████████▉ | 1523/1710 [13:08<01:32,  2.01it/s]
 89%|████████▉ | 1524/1710 [13:08<01:28,  2.10it/s]
 89%|████████▉ | 1525/1710 [13:09<01:27,  2.11it/s]
 89%|████████▉ | 1526/1710 [13:09<01:21,  2.25it/s]
 89%|████████▉ | 1527/1710 [13:09<01:16,  2.38it/s]
 89%|████████▉ | 1528/1710 [13:10<01:15,  2.41it/s]
 89%|████████▉ | 1529/1710 [13:10<01:15,  2.39it/s]
 89%|████████▉ | 1530/1710 [13:11<01:12,  2.47it/s]
 90%|████████▉ | 1531/1710 [13:11<01:08,  2.61it/s]
 90%|████████▉ | 1532/1710 [13:11<01:13,  2.42it/s]
 90%|████████▉ | 1533/1710 [13:12<01:21,  2.17it/s]
 90%|████████▉ | 1534/1710 [13:13<01:27,  2.02it/s]
 90%|████████▉ | 1535/1710 [13:13<01:23,  2.11it/s]
 90%|████████▉ | 1536/1710 [13:14<01:22,  2.11it/s]
 90%|████████▉ | 1537/1710 [13:14<01:19,  2.18it/s]
 90%|████████▉ | 1538/1710 [13:14<01:17,  2.23it/s]
 90%|█████████ | 1539/1710 [13:15<01:15,  2.26it/s][INFO|trainer.py:811] 2024-09-09 12:28:10,968 >> The following columns in the evaluation set don't have a corresponding argument in `RobertaForTokenClassification.forward` and have been ignored: ner_tags, id, tokens. If ner_tags, id, tokens are not expected by `RobertaForTokenClassification.forward`,  you can safely ignore this message.
+[INFO|trainer.py:3819] 2024-09-09 12:28:10,970 >> 
+***** Running Evaluation *****
+[INFO|trainer.py:3821] 2024-09-09 12:28:10,970 >>   Num examples = 2519
+[INFO|trainer.py:3824] 2024-09-09 12:28:10,970 >>   Batch size = 8
+{'eval_loss': 0.28080618381500244, 'eval_precision': 0.6529382219989954, 'eval_recall': 0.7115489874110563, 'eval_f1': 0.680984808800419, 'eval_accuracy': 0.9473354935994097, 'eval_runtime': 5.9073, 'eval_samples_per_second': 426.421, 'eval_steps_per_second': 53.324, 'epoch': 8.0}
+{'loss': 0.0082, 'grad_norm': 0.22467799484729767, 'learning_rate': 6.140350877192982e-06, 'epoch': 8.77}
+
+
  0%|          | 0/315 [00:00<?, ?it/s]
+
  3%|▎         | 8/315 [00:00<00:03, 78.15it/s]
+
  5%|▌         | 16/315 [00:00<00:03, 75.10it/s]
+
  8%|▊         | 24/315 [00:00<00:03, 76.23it/s]
+
 10%|█         | 32/315 [00:00<00:03, 72.03it/s]
+
 13%|█▎        | 41/315 [00:00<00:03, 75.31it/s]
+
 16%|█▌        | 49/315 [00:00<00:03, 74.22it/s]
+
 18%|█▊        | 57/315 [00:00<00:03, 74.53it/s]
+
 21%|██        | 65/315 [00:00<00:03, 71.62it/s]
+
 23%|██▎       | 73/315 [00:00<00:03, 73.27it/s]
+
 26%|██▌       | 81/315 [00:01<00:03, 69.11it/s]
+
 28%|██▊       | 88/315 [00:01<00:03, 66.88it/s]
+
 30%|███       | 96/315 [00:01<00:03, 70.07it/s]
+
 33%|███▎      | 104/315 [00:01<00:03, 67.39it/s]
+
 36%|███▌      | 112/315 [00:01<00:02, 69.18it/s]
+
 38%|███▊      | 120/315 [00:01<00:02, 68.81it/s]
+
 40%|████      | 127/315 [00:01<00:02, 68.85it/s]
+
 43%|████▎     | 134/315 [00:01<00:02, 68.15it/s]
+
 45%|████▍     | 141/315 [00:01<00:02, 68.66it/s]
+
 47%|████▋     | 149/315 [00:02<00:02, 71.11it/s]
+
 50%|████▉     | 157/315 [00:02<00:02, 73.67it/s]
+
 52%|█████▏    | 165/315 [00:02<00:02, 72.41it/s]
+
 55%|█████▍    | 173/315 [00:02<00:01, 71.77it/s]
+
 57%|█████▋    | 181/315 [00:02<00:01, 69.01it/s]
+
 60%|██████    | 189/315 [00:02<00:01, 68.89it/s]
+
 62%|██████▏   | 196/315 [00:02<00:01, 67.87it/s]
+
 64%|██████▍   | 203/315 [00:02<00:01, 65.16it/s]
+
 67%|██████▋   | 210/315 [00:03<00:01, 65.43it/s]
+
 69%|██████▉   | 218/315 [00:03<00:01, 69.24it/s]
+
 72%|███████▏  | 226/315 [00:03<00:01, 71.30it/s]
+
 75%|███████▍  | 235/315 [00:03<00:01, 74.27it/s]
+
 77%|███████▋  | 243/315 [00:03<00:01, 70.36it/s]
+
 80%|███████▉  | 251/315 [00:03<00:00, 70.27it/s]
+
 82%|████████▏ | 259/315 [00:03<00:00, 69.06it/s]
+
 85%|████████▍ | 267/315 [00:03<00:00, 70.31it/s]
+
 88%|████████▊ | 276/315 [00:03<00:00, 73.18it/s]
+
 90%|█████████ | 284/315 [00:04<00:00, 73.60it/s]
+
 93%|█████████▎| 292/315 [00:04<00:00, 70.96it/s]
+
 95%|█████████▌| 300/315 [00:04<00:00, 70.32it/s]
+
 98%|█████████▊| 308/315 [00:04<00:00, 70.86it/s]
                                                   
+
                                                 
 90%|█████████ | 1539/1710 [13:21<01:15,  2.26it/s]
+
+
                                                 [INFO|trainer.py:3503] 2024-09-09 12:28:16,907 >> Saving model checkpoint to /content/dissertation/scripts/ner/output/checkpoint-1539
+[INFO|configuration_utils.py:472] 2024-09-09 12:28:16,908 >> Configuration saved in /content/dissertation/scripts/ner/output/checkpoint-1539/config.json
+[INFO|modeling_utils.py:2799] 2024-09-09 12:28:17,937 >> Model weights saved in /content/dissertation/scripts/ner/output/checkpoint-1539/model.safetensors
+[INFO|tokenization_utils_base.py:2684] 2024-09-09 12:28:17,938 >> tokenizer config file saved in /content/dissertation/scripts/ner/output/checkpoint-1539/tokenizer_config.json
+[INFO|tokenization_utils_base.py:2693] 2024-09-09 12:28:17,939 >> Special tokens file saved in /content/dissertation/scripts/ner/output/checkpoint-1539/special_tokens_map.json
+[INFO|tokenization_utils_base.py:2684] 2024-09-09 12:28:22,554 >> tokenizer config file saved in /content/dissertation/scripts/ner/output/tokenizer_config.json
+[INFO|tokenization_utils_base.py:2693] 2024-09-09 12:28:22,555 >> Special tokens file saved in /content/dissertation/scripts/ner/output/special_tokens_map.json
+
 90%|█████████ | 1540/1710 [13:27<11:03,  3.90s/it]
 90%|█████████ | 1541/1710 [13:27<08:00,  2.85s/it]
 90%|█████████ | 1542/1710 [13:28<05:53,  2.11s/it]
 90%|█████████ | 1543/1710 [13:28<04:32,  1.63s/it]
 90%|█████████ | 1544/1710 [13:29<03:37,  1.31s/it]
 90%|█████████ | 1545/1710 [13:29<02:50,  1.03s/it]
 90%|█████████ | 1546/1710 [13:29<02:18,  1.18it/s]
 90%|█████████ | 1547/1710 [13:30<01:55,  1.41it/s]
 91%|█████████ | 1548/1710 [13:30<01:37,  1.66it/s]
 91%|█████████ | 1549/1710 [13:31<01:27,  1.84it/s]
 91%|█████████ | 1550/1710 [13:31<01:19,  2.01it/s]
 91%|█████████ | 1551/1710 [13:32<01:31,  1.74it/s]
 91%|█████████ | 1552/1710 [13:32<01:23,  1.90it/s]
 91%|█████████ | 1553/1710 [13:33<01:15,  2.09it/s]
 91%|█████████ | 1554/1710 [13:33<01:17,  2.00it/s]
 91%|█████████ | 1555/1710 [13:34<01:16,  2.02it/s]
 91%|█████████ | 1556/1710 [13:34<01:12,  2.13it/s]
 91%|█████████ | 1557/1710 [13:34<01:10,  2.17it/s]
 91%|█████████ | 1558/1710 [13:35<01:05,  2.31it/s]
 91%|█████████ | 1559/1710 [13:35<01:05,  2.29it/s]
 91%|█████████ | 1560/1710 [13:36<01:04,  2.34it/s]
 91%|█████████▏| 1561/1710 [13:36<01:03,  2.35it/s]
 91%|█████████▏| 1562/1710 [13:36<01:00,  2.44it/s]
 91%|█████████▏| 1563/1710 [13:37<00:58,  2.50it/s]
 91%|█████████▏| 1564/1710 [13:37<00:58,  2.52it/s]
 92%|█████████▏| 1565/1710 [13:38<00:59,  2.44it/s]
 92%|█████████▏| 1566/1710 [13:38<00:56,  2.55it/s]
 92%|█████████▏| 1567/1710 [13:39<01:06,  2.14it/s]
 92%|█████████▏| 1568/1710 [13:40<01:28,  1.60it/s]
 92%|█████████▏| 1569/1710 [13:40<01:26,  1.63it/s]
 92%|█████████▏| 1570/1710 [13:41<01:13,  1.90it/s]
 92%|█████████▏| 1571/1710 [13:41<01:04,  2.16it/s]
 92%|█████████▏| 1572/1710 [13:42<01:26,  1.60it/s]
 92%|█████████▏| 1573/1710 [13:42<01:13,  1.86it/s]
 92%|█████████▏| 1574/1710 [13:43<01:08,  1.99it/s]
 92%|█████████▏| 1575/1710 [13:43<01:04,  2.09it/s]
 92%|█████████▏| 1576/1710 [13:43<01:03,  2.13it/s]
 92%|█████████▏| 1577/1710 [13:44<00:57,  2.32it/s]
 92%|█████████▏| 1578/1710 [13:44<00:53,  2.45it/s]
 92%|████████��▏| 1579/1710 [13:45<00:55,  2.34it/s]
 92%|█████████▏| 1580/1710 [13:45<00:55,  2.33it/s]
 92%|█████████▏| 1581/1710 [13:45<00:55,  2.32it/s]
 93%|█████████▎| 1582/1710 [13:46<00:54,  2.36it/s]
 93%|█████████▎| 1583/1710 [13:46<00:54,  2.34it/s]
 93%|█████████▎| 1584/1710 [13:47<00:54,  2.33it/s]
 93%|█████████▎| 1585/1710 [13:47<01:01,  2.03it/s]
 93%|█████████▎| 1586/1710 [13:48<00:58,  2.12it/s]
 93%|█████████▎| 1587/1710 [13:48<00:54,  2.27it/s]
 93%|█████████▎| 1588/1710 [13:49<00:54,  2.25it/s]
 93%|█████████▎| 1589/1710 [13:49<01:01,  1.98it/s]