Upload folder using huggingface_hub

#4
by CreatorPhan - opened
Files changed (5) hide show
  1. adapter_model.bin +1 -1
  2. optimizer.pt +1 -1
  3. rng_state.pth +1 -1
  4. scheduler.pt +1 -1
  5. trainer_state.json +1803 -3
adapter_model.bin CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:8beb03e0dedfb5b2da0d68ebcc49dbb502cea67ba9c0d70bed474bdde253aa1d
3
  size 39409357
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:0bfdd727772683806731fba15bf8f4caf691af6184bc5b21e2ea5a4f390f41dc
3
  size 39409357
optimizer.pt CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:745db72555229d45c6a69054bcdee18c9e9f3193c81ae335546612e8aaa6d7c4
3
  size 78844421
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:c80d296d52ab4d4c11a0695940c0dadb792928e126cde3111312316dd3d33438
3
  size 78844421
rng_state.pth CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:6162bb9db25c89c41e126a7a00a5d0695219447bff9b18d08731531620758440
3
  size 14575
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:3e46ce4eb16240da9f3a8b3066acb6f59a234249ee2a3052f3323786da479838
3
  size 14575
scheduler.pt CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:461382c4e71db35cef694681fd3a0c229adb91f6f9d1e458e9d3c9be9149f8c4
3
  size 627
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:64035578adb33297a89b3be176cbd0b7d7adb0f34d904267be99bb01d2a849d0
3
  size 627
trainer_state.json CHANGED
@@ -1,9 +1,9 @@
1
  {
2
  "best_metric": null,
3
  "best_model_checkpoint": null,
4
- "epoch": 5.714285714285714,
5
  "eval_steps": 500,
6
- "global_step": 200,
7
  "is_hyper_param_search": false,
8
  "is_local_process_zero": true,
9
  "is_world_process_zero": true,
@@ -1207,13 +1207,1813 @@
1207
  "learning_rate": 0.002642857142857143,
1208
  "loss": 1.678,
1209
  "step": 200
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1210
  }
1211
  ],
1212
  "logging_steps": 1,
1213
  "max_steps": 1680,
1214
  "num_train_epochs": 48,
1215
  "save_steps": 100,
1216
- "total_flos": 1.1559978611371008e+17,
1217
  "trial_name": null,
1218
  "trial_params": null
1219
  }
 
1
  {
2
  "best_metric": null,
3
  "best_model_checkpoint": null,
4
+ "epoch": 14.285714285714286,
5
  "eval_steps": 500,
6
+ "global_step": 500,
7
  "is_hyper_param_search": false,
8
  "is_local_process_zero": true,
9
  "is_world_process_zero": true,
 
1207
  "learning_rate": 0.002642857142857143,
1208
  "loss": 1.678,
1209
  "step": 200
1210
+ },
1211
+ {
1212
+ "epoch": 5.74,
1213
+ "learning_rate": 0.0026410714285714284,
1214
+ "loss": 1.7613,
1215
+ "step": 201
1216
+ },
1217
+ {
1218
+ "epoch": 5.77,
1219
+ "learning_rate": 0.0026392857142857142,
1220
+ "loss": 1.7541,
1221
+ "step": 202
1222
+ },
1223
+ {
1224
+ "epoch": 5.8,
1225
+ "learning_rate": 0.0026375,
1226
+ "loss": 1.798,
1227
+ "step": 203
1228
+ },
1229
+ {
1230
+ "epoch": 5.83,
1231
+ "learning_rate": 0.002635714285714286,
1232
+ "loss": 1.821,
1233
+ "step": 204
1234
+ },
1235
+ {
1236
+ "epoch": 5.86,
1237
+ "learning_rate": 0.0026339285714285714,
1238
+ "loss": 1.8385,
1239
+ "step": 205
1240
+ },
1241
+ {
1242
+ "epoch": 5.89,
1243
+ "learning_rate": 0.002632142857142857,
1244
+ "loss": 1.8613,
1245
+ "step": 206
1246
+ },
1247
+ {
1248
+ "epoch": 5.91,
1249
+ "learning_rate": 0.002630357142857143,
1250
+ "loss": 1.902,
1251
+ "step": 207
1252
+ },
1253
+ {
1254
+ "epoch": 5.94,
1255
+ "learning_rate": 0.0026285714285714285,
1256
+ "loss": 2.0848,
1257
+ "step": 208
1258
+ },
1259
+ {
1260
+ "epoch": 5.97,
1261
+ "learning_rate": 0.0026267857142857143,
1262
+ "loss": 2.3277,
1263
+ "step": 209
1264
+ },
1265
+ {
1266
+ "epoch": 6.0,
1267
+ "learning_rate": 0.002625,
1268
+ "loss": 2.8535,
1269
+ "step": 210
1270
+ },
1271
+ {
1272
+ "epoch": 6.03,
1273
+ "learning_rate": 0.0026232142857142856,
1274
+ "loss": 6.2197,
1275
+ "step": 211
1276
+ },
1277
+ {
1278
+ "epoch": 6.06,
1279
+ "learning_rate": 0.0026214285714285714,
1280
+ "loss": 10.2288,
1281
+ "step": 212
1282
+ },
1283
+ {
1284
+ "epoch": 6.09,
1285
+ "learning_rate": 0.0026196428571428573,
1286
+ "loss": 12.5006,
1287
+ "step": 213
1288
+ },
1289
+ {
1290
+ "epoch": 6.11,
1291
+ "learning_rate": 0.002617857142857143,
1292
+ "loss": 10.5184,
1293
+ "step": 214
1294
+ },
1295
+ {
1296
+ "epoch": 6.14,
1297
+ "learning_rate": 0.0026160714285714285,
1298
+ "loss": 9.4834,
1299
+ "step": 215
1300
+ },
1301
+ {
1302
+ "epoch": 6.17,
1303
+ "learning_rate": 0.0026142857142857144,
1304
+ "loss": 16.0513,
1305
+ "step": 216
1306
+ },
1307
+ {
1308
+ "epoch": 6.2,
1309
+ "learning_rate": 0.0026125000000000002,
1310
+ "loss": 11.0576,
1311
+ "step": 217
1312
+ },
1313
+ {
1314
+ "epoch": 6.23,
1315
+ "learning_rate": 0.0026107142857142857,
1316
+ "loss": 15.3574,
1317
+ "step": 218
1318
+ },
1319
+ {
1320
+ "epoch": 6.26,
1321
+ "learning_rate": 0.0026089285714285715,
1322
+ "loss": 15.5239,
1323
+ "step": 219
1324
+ },
1325
+ {
1326
+ "epoch": 6.29,
1327
+ "learning_rate": 0.0026071428571428574,
1328
+ "loss": 15.3973,
1329
+ "step": 220
1330
+ },
1331
+ {
1332
+ "epoch": 6.31,
1333
+ "learning_rate": 0.0026053571428571428,
1334
+ "loss": 12.059,
1335
+ "step": 221
1336
+ },
1337
+ {
1338
+ "epoch": 6.34,
1339
+ "learning_rate": 0.0026035714285714286,
1340
+ "loss": 10.8352,
1341
+ "step": 222
1342
+ },
1343
+ {
1344
+ "epoch": 6.37,
1345
+ "learning_rate": 0.0026017857142857145,
1346
+ "loss": 10.1507,
1347
+ "step": 223
1348
+ },
1349
+ {
1350
+ "epoch": 6.4,
1351
+ "learning_rate": 0.0026000000000000003,
1352
+ "loss": 10.651,
1353
+ "step": 224
1354
+ },
1355
+ {
1356
+ "epoch": 6.43,
1357
+ "learning_rate": 0.0025982142857142857,
1358
+ "loss": 9.8363,
1359
+ "step": 225
1360
+ },
1361
+ {
1362
+ "epoch": 6.46,
1363
+ "learning_rate": 0.0025964285714285716,
1364
+ "loss": 9.3673,
1365
+ "step": 226
1366
+ },
1367
+ {
1368
+ "epoch": 6.49,
1369
+ "learning_rate": 0.0025946428571428574,
1370
+ "loss": 9.5433,
1371
+ "step": 227
1372
+ },
1373
+ {
1374
+ "epoch": 6.51,
1375
+ "learning_rate": 0.002592857142857143,
1376
+ "loss": 9.9206,
1377
+ "step": 228
1378
+ },
1379
+ {
1380
+ "epoch": 6.54,
1381
+ "learning_rate": 0.0025910714285714287,
1382
+ "loss": 9.5516,
1383
+ "step": 229
1384
+ },
1385
+ {
1386
+ "epoch": 6.57,
1387
+ "learning_rate": 0.0025892857142857145,
1388
+ "loss": 9.2165,
1389
+ "step": 230
1390
+ },
1391
+ {
1392
+ "epoch": 6.6,
1393
+ "learning_rate": 0.0025875000000000004,
1394
+ "loss": 9.0825,
1395
+ "step": 231
1396
+ },
1397
+ {
1398
+ "epoch": 6.63,
1399
+ "learning_rate": 0.002585714285714286,
1400
+ "loss": 8.7437,
1401
+ "step": 232
1402
+ },
1403
+ {
1404
+ "epoch": 6.66,
1405
+ "learning_rate": 0.0025839285714285717,
1406
+ "loss": 8.6366,
1407
+ "step": 233
1408
+ },
1409
+ {
1410
+ "epoch": 6.69,
1411
+ "learning_rate": 0.0025821428571428575,
1412
+ "loss": 9.7431,
1413
+ "step": 234
1414
+ },
1415
+ {
1416
+ "epoch": 6.71,
1417
+ "learning_rate": 0.002580357142857143,
1418
+ "loss": 8.1876,
1419
+ "step": 235
1420
+ },
1421
+ {
1422
+ "epoch": 6.74,
1423
+ "learning_rate": 0.0025785714285714288,
1424
+ "loss": 8.4559,
1425
+ "step": 236
1426
+ },
1427
+ {
1428
+ "epoch": 6.77,
1429
+ "learning_rate": 0.002576785714285714,
1430
+ "loss": 8.0092,
1431
+ "step": 237
1432
+ },
1433
+ {
1434
+ "epoch": 6.8,
1435
+ "learning_rate": 0.002575,
1436
+ "loss": 8.028,
1437
+ "step": 238
1438
+ },
1439
+ {
1440
+ "epoch": 6.83,
1441
+ "learning_rate": 0.0025732142857142854,
1442
+ "loss": 7.8379,
1443
+ "step": 239
1444
+ },
1445
+ {
1446
+ "epoch": 6.86,
1447
+ "learning_rate": 0.0025714285714285713,
1448
+ "loss": 7.8127,
1449
+ "step": 240
1450
+ },
1451
+ {
1452
+ "epoch": 6.89,
1453
+ "learning_rate": 0.002569642857142857,
1454
+ "loss": 7.8252,
1455
+ "step": 241
1456
+ },
1457
+ {
1458
+ "epoch": 6.91,
1459
+ "learning_rate": 0.002567857142857143,
1460
+ "loss": 7.7094,
1461
+ "step": 242
1462
+ },
1463
+ {
1464
+ "epoch": 6.94,
1465
+ "learning_rate": 0.0025660714285714284,
1466
+ "loss": 7.7962,
1467
+ "step": 243
1468
+ },
1469
+ {
1470
+ "epoch": 6.97,
1471
+ "learning_rate": 0.0025642857142857143,
1472
+ "loss": 7.4966,
1473
+ "step": 244
1474
+ },
1475
+ {
1476
+ "epoch": 7.0,
1477
+ "learning_rate": 0.0025625,
1478
+ "loss": 7.4851,
1479
+ "step": 245
1480
+ },
1481
+ {
1482
+ "epoch": 7.03,
1483
+ "learning_rate": 0.0025607142857142855,
1484
+ "loss": 7.5188,
1485
+ "step": 246
1486
+ },
1487
+ {
1488
+ "epoch": 7.06,
1489
+ "learning_rate": 0.0025589285714285714,
1490
+ "loss": 7.7866,
1491
+ "step": 247
1492
+ },
1493
+ {
1494
+ "epoch": 7.09,
1495
+ "learning_rate": 0.0025571428571428572,
1496
+ "loss": 7.5743,
1497
+ "step": 248
1498
+ },
1499
+ {
1500
+ "epoch": 7.11,
1501
+ "learning_rate": 0.0025553571428571426,
1502
+ "loss": 7.4608,
1503
+ "step": 249
1504
+ },
1505
+ {
1506
+ "epoch": 7.14,
1507
+ "learning_rate": 0.0025535714285714285,
1508
+ "loss": 7.4655,
1509
+ "step": 250
1510
+ },
1511
+ {
1512
+ "epoch": 7.17,
1513
+ "learning_rate": 0.0025517857142857143,
1514
+ "loss": 7.5474,
1515
+ "step": 251
1516
+ },
1517
+ {
1518
+ "epoch": 7.2,
1519
+ "learning_rate": 0.00255,
1520
+ "loss": 7.6983,
1521
+ "step": 252
1522
+ },
1523
+ {
1524
+ "epoch": 7.23,
1525
+ "learning_rate": 0.0025482142857142856,
1526
+ "loss": 7.4936,
1527
+ "step": 253
1528
+ },
1529
+ {
1530
+ "epoch": 7.26,
1531
+ "learning_rate": 0.0025464285714285714,
1532
+ "loss": 7.6966,
1533
+ "step": 254
1534
+ },
1535
+ {
1536
+ "epoch": 7.29,
1537
+ "learning_rate": 0.0025446428571428573,
1538
+ "loss": 7.4701,
1539
+ "step": 255
1540
+ },
1541
+ {
1542
+ "epoch": 7.31,
1543
+ "learning_rate": 0.0025428571428571427,
1544
+ "loss": 7.511,
1545
+ "step": 256
1546
+ },
1547
+ {
1548
+ "epoch": 7.34,
1549
+ "learning_rate": 0.0025410714285714286,
1550
+ "loss": 7.3709,
1551
+ "step": 257
1552
+ },
1553
+ {
1554
+ "epoch": 7.37,
1555
+ "learning_rate": 0.0025392857142857144,
1556
+ "loss": 7.4582,
1557
+ "step": 258
1558
+ },
1559
+ {
1560
+ "epoch": 7.4,
1561
+ "learning_rate": 0.0025375,
1562
+ "loss": 7.4263,
1563
+ "step": 259
1564
+ },
1565
+ {
1566
+ "epoch": 7.43,
1567
+ "learning_rate": 0.0025357142857142857,
1568
+ "loss": 7.3134,
1569
+ "step": 260
1570
+ },
1571
+ {
1572
+ "epoch": 7.46,
1573
+ "learning_rate": 0.0025339285714285715,
1574
+ "loss": 7.3849,
1575
+ "step": 261
1576
+ },
1577
+ {
1578
+ "epoch": 7.49,
1579
+ "learning_rate": 0.0025321428571428574,
1580
+ "loss": 7.292,
1581
+ "step": 262
1582
+ },
1583
+ {
1584
+ "epoch": 7.51,
1585
+ "learning_rate": 0.002530357142857143,
1586
+ "loss": 7.343,
1587
+ "step": 263
1588
+ },
1589
+ {
1590
+ "epoch": 7.54,
1591
+ "learning_rate": 0.0025285714285714286,
1592
+ "loss": 7.3166,
1593
+ "step": 264
1594
+ },
1595
+ {
1596
+ "epoch": 7.57,
1597
+ "learning_rate": 0.0025267857142857145,
1598
+ "loss": 7.2676,
1599
+ "step": 265
1600
+ },
1601
+ {
1602
+ "epoch": 7.6,
1603
+ "learning_rate": 0.002525,
1604
+ "loss": 7.2955,
1605
+ "step": 266
1606
+ },
1607
+ {
1608
+ "epoch": 7.63,
1609
+ "learning_rate": 0.0025232142857142857,
1610
+ "loss": 7.3386,
1611
+ "step": 267
1612
+ },
1613
+ {
1614
+ "epoch": 7.66,
1615
+ "learning_rate": 0.0025214285714285716,
1616
+ "loss": 7.2682,
1617
+ "step": 268
1618
+ },
1619
+ {
1620
+ "epoch": 7.69,
1621
+ "learning_rate": 0.0025196428571428574,
1622
+ "loss": 7.2359,
1623
+ "step": 269
1624
+ },
1625
+ {
1626
+ "epoch": 7.71,
1627
+ "learning_rate": 0.002517857142857143,
1628
+ "loss": 7.1849,
1629
+ "step": 270
1630
+ },
1631
+ {
1632
+ "epoch": 7.74,
1633
+ "learning_rate": 0.0025160714285714287,
1634
+ "loss": 7.2421,
1635
+ "step": 271
1636
+ },
1637
+ {
1638
+ "epoch": 7.77,
1639
+ "learning_rate": 0.0025142857142857146,
1640
+ "loss": 7.2341,
1641
+ "step": 272
1642
+ },
1643
+ {
1644
+ "epoch": 7.8,
1645
+ "learning_rate": 0.0025125,
1646
+ "loss": 7.2901,
1647
+ "step": 273
1648
+ },
1649
+ {
1650
+ "epoch": 7.83,
1651
+ "learning_rate": 0.002510714285714286,
1652
+ "loss": 7.1931,
1653
+ "step": 274
1654
+ },
1655
+ {
1656
+ "epoch": 7.86,
1657
+ "learning_rate": 0.0025089285714285717,
1658
+ "loss": 7.1907,
1659
+ "step": 275
1660
+ },
1661
+ {
1662
+ "epoch": 7.89,
1663
+ "learning_rate": 0.002507142857142857,
1664
+ "loss": 7.2369,
1665
+ "step": 276
1666
+ },
1667
+ {
1668
+ "epoch": 7.91,
1669
+ "learning_rate": 0.002505357142857143,
1670
+ "loss": 7.1764,
1671
+ "step": 277
1672
+ },
1673
+ {
1674
+ "epoch": 7.94,
1675
+ "learning_rate": 0.002503571428571429,
1676
+ "loss": 7.1928,
1677
+ "step": 278
1678
+ },
1679
+ {
1680
+ "epoch": 7.97,
1681
+ "learning_rate": 0.0025017857142857146,
1682
+ "loss": 7.2114,
1683
+ "step": 279
1684
+ },
1685
+ {
1686
+ "epoch": 8.0,
1687
+ "learning_rate": 0.0025,
1688
+ "loss": 7.2307,
1689
+ "step": 280
1690
+ },
1691
+ {
1692
+ "epoch": 8.03,
1693
+ "learning_rate": 0.002498214285714286,
1694
+ "loss": 7.2477,
1695
+ "step": 281
1696
+ },
1697
+ {
1698
+ "epoch": 8.06,
1699
+ "learning_rate": 0.0024964285714285718,
1700
+ "loss": 7.2069,
1701
+ "step": 282
1702
+ },
1703
+ {
1704
+ "epoch": 8.09,
1705
+ "learning_rate": 0.002494642857142857,
1706
+ "loss": 7.1484,
1707
+ "step": 283
1708
+ },
1709
+ {
1710
+ "epoch": 8.11,
1711
+ "learning_rate": 0.002492857142857143,
1712
+ "loss": 7.1076,
1713
+ "step": 284
1714
+ },
1715
+ {
1716
+ "epoch": 8.14,
1717
+ "learning_rate": 0.002491071428571429,
1718
+ "loss": 7.0819,
1719
+ "step": 285
1720
+ },
1721
+ {
1722
+ "epoch": 8.17,
1723
+ "learning_rate": 0.0024892857142857143,
1724
+ "loss": 7.0708,
1725
+ "step": 286
1726
+ },
1727
+ {
1728
+ "epoch": 8.2,
1729
+ "learning_rate": 0.0024875,
1730
+ "loss": 7.0763,
1731
+ "step": 287
1732
+ },
1733
+ {
1734
+ "epoch": 8.23,
1735
+ "learning_rate": 0.002485714285714286,
1736
+ "loss": 7.0792,
1737
+ "step": 288
1738
+ },
1739
+ {
1740
+ "epoch": 8.26,
1741
+ "learning_rate": 0.0024839285714285714,
1742
+ "loss": 7.1397,
1743
+ "step": 289
1744
+ },
1745
+ {
1746
+ "epoch": 8.29,
1747
+ "learning_rate": 0.0024821428571428572,
1748
+ "loss": 7.0893,
1749
+ "step": 290
1750
+ },
1751
+ {
1752
+ "epoch": 8.31,
1753
+ "learning_rate": 0.0024803571428571427,
1754
+ "loss": 7.1263,
1755
+ "step": 291
1756
+ },
1757
+ {
1758
+ "epoch": 8.34,
1759
+ "learning_rate": 0.0024785714285714285,
1760
+ "loss": 7.0226,
1761
+ "step": 292
1762
+ },
1763
+ {
1764
+ "epoch": 8.37,
1765
+ "learning_rate": 0.0024767857142857144,
1766
+ "loss": 7.1017,
1767
+ "step": 293
1768
+ },
1769
+ {
1770
+ "epoch": 8.4,
1771
+ "learning_rate": 0.0024749999999999998,
1772
+ "loss": 7.0161,
1773
+ "step": 294
1774
+ },
1775
+ {
1776
+ "epoch": 8.43,
1777
+ "learning_rate": 0.0024732142857142856,
1778
+ "loss": 7.117,
1779
+ "step": 295
1780
+ },
1781
+ {
1782
+ "epoch": 8.46,
1783
+ "learning_rate": 0.0024714285714285715,
1784
+ "loss": 7.0234,
1785
+ "step": 296
1786
+ },
1787
+ {
1788
+ "epoch": 8.49,
1789
+ "learning_rate": 0.002469642857142857,
1790
+ "loss": 7.0663,
1791
+ "step": 297
1792
+ },
1793
+ {
1794
+ "epoch": 8.51,
1795
+ "learning_rate": 0.0024678571428571427,
1796
+ "loss": 7.1604,
1797
+ "step": 298
1798
+ },
1799
+ {
1800
+ "epoch": 8.54,
1801
+ "learning_rate": 0.0024660714285714286,
1802
+ "loss": 7.0543,
1803
+ "step": 299
1804
+ },
1805
+ {
1806
+ "epoch": 8.57,
1807
+ "learning_rate": 0.0024642857142857144,
1808
+ "loss": 7.0131,
1809
+ "step": 300
1810
+ },
1811
+ {
1812
+ "epoch": 8.6,
1813
+ "learning_rate": 0.0024625,
1814
+ "loss": 7.0294,
1815
+ "step": 301
1816
+ },
1817
+ {
1818
+ "epoch": 8.63,
1819
+ "learning_rate": 0.0024607142857142857,
1820
+ "loss": 7.0273,
1821
+ "step": 302
1822
+ },
1823
+ {
1824
+ "epoch": 8.66,
1825
+ "learning_rate": 0.0024589285714285715,
1826
+ "loss": 7.0074,
1827
+ "step": 303
1828
+ },
1829
+ {
1830
+ "epoch": 8.69,
1831
+ "learning_rate": 0.002457142857142857,
1832
+ "loss": 6.9747,
1833
+ "step": 304
1834
+ },
1835
+ {
1836
+ "epoch": 8.71,
1837
+ "learning_rate": 0.002455357142857143,
1838
+ "loss": 7.0617,
1839
+ "step": 305
1840
+ },
1841
+ {
1842
+ "epoch": 8.74,
1843
+ "learning_rate": 0.0024535714285714287,
1844
+ "loss": 7.0907,
1845
+ "step": 306
1846
+ },
1847
+ {
1848
+ "epoch": 8.77,
1849
+ "learning_rate": 0.002451785714285714,
1850
+ "loss": 7.0037,
1851
+ "step": 307
1852
+ },
1853
+ {
1854
+ "epoch": 8.8,
1855
+ "learning_rate": 0.00245,
1856
+ "loss": 6.969,
1857
+ "step": 308
1858
+ },
1859
+ {
1860
+ "epoch": 8.83,
1861
+ "learning_rate": 0.0024482142857142858,
1862
+ "loss": 7.0575,
1863
+ "step": 309
1864
+ },
1865
+ {
1866
+ "epoch": 8.86,
1867
+ "learning_rate": 0.0024464285714285716,
1868
+ "loss": 6.9494,
1869
+ "step": 310
1870
+ },
1871
+ {
1872
+ "epoch": 8.89,
1873
+ "learning_rate": 0.002444642857142857,
1874
+ "loss": 6.969,
1875
+ "step": 311
1876
+ },
1877
+ {
1878
+ "epoch": 8.91,
1879
+ "learning_rate": 0.002442857142857143,
1880
+ "loss": 6.8827,
1881
+ "step": 312
1882
+ },
1883
+ {
1884
+ "epoch": 8.94,
1885
+ "learning_rate": 0.0024410714285714287,
1886
+ "loss": 6.9058,
1887
+ "step": 313
1888
+ },
1889
+ {
1890
+ "epoch": 8.97,
1891
+ "learning_rate": 0.002439285714285714,
1892
+ "loss": 6.8808,
1893
+ "step": 314
1894
+ },
1895
+ {
1896
+ "epoch": 9.0,
1897
+ "learning_rate": 0.0024375,
1898
+ "loss": 6.9516,
1899
+ "step": 315
1900
+ },
1901
+ {
1902
+ "epoch": 9.03,
1903
+ "learning_rate": 0.002435714285714286,
1904
+ "loss": 6.9132,
1905
+ "step": 316
1906
+ },
1907
+ {
1908
+ "epoch": 9.06,
1909
+ "learning_rate": 0.0024339285714285717,
1910
+ "loss": 6.9058,
1911
+ "step": 317
1912
+ },
1913
+ {
1914
+ "epoch": 9.09,
1915
+ "learning_rate": 0.002432142857142857,
1916
+ "loss": 6.9332,
1917
+ "step": 318
1918
+ },
1919
+ {
1920
+ "epoch": 9.11,
1921
+ "learning_rate": 0.002430357142857143,
1922
+ "loss": 6.9757,
1923
+ "step": 319
1924
+ },
1925
+ {
1926
+ "epoch": 9.14,
1927
+ "learning_rate": 0.002428571428571429,
1928
+ "loss": 6.8261,
1929
+ "step": 320
1930
+ },
1931
+ {
1932
+ "epoch": 9.17,
1933
+ "learning_rate": 0.0024267857142857142,
1934
+ "loss": 6.8571,
1935
+ "step": 321
1936
+ },
1937
+ {
1938
+ "epoch": 9.2,
1939
+ "learning_rate": 0.002425,
1940
+ "loss": 6.8435,
1941
+ "step": 322
1942
+ },
1943
+ {
1944
+ "epoch": 9.23,
1945
+ "learning_rate": 0.002423214285714286,
1946
+ "loss": 6.9033,
1947
+ "step": 323
1948
+ },
1949
+ {
1950
+ "epoch": 9.26,
1951
+ "learning_rate": 0.0024214285714285713,
1952
+ "loss": 6.8042,
1953
+ "step": 324
1954
+ },
1955
+ {
1956
+ "epoch": 9.29,
1957
+ "learning_rate": 0.002419642857142857,
1958
+ "loss": 6.8732,
1959
+ "step": 325
1960
+ },
1961
+ {
1962
+ "epoch": 9.31,
1963
+ "learning_rate": 0.002417857142857143,
1964
+ "loss": 6.752,
1965
+ "step": 326
1966
+ },
1967
+ {
1968
+ "epoch": 9.34,
1969
+ "learning_rate": 0.002416071428571429,
1970
+ "loss": 6.8016,
1971
+ "step": 327
1972
+ },
1973
+ {
1974
+ "epoch": 9.37,
1975
+ "learning_rate": 0.0024142857142857143,
1976
+ "loss": 6.8879,
1977
+ "step": 328
1978
+ },
1979
+ {
1980
+ "epoch": 9.4,
1981
+ "learning_rate": 0.0024125,
1982
+ "loss": 6.7643,
1983
+ "step": 329
1984
+ },
1985
+ {
1986
+ "epoch": 9.43,
1987
+ "learning_rate": 0.002410714285714286,
1988
+ "loss": 6.7084,
1989
+ "step": 330
1990
+ },
1991
+ {
1992
+ "epoch": 9.46,
1993
+ "learning_rate": 0.0024089285714285714,
1994
+ "loss": 6.8049,
1995
+ "step": 331
1996
+ },
1997
+ {
1998
+ "epoch": 9.49,
1999
+ "learning_rate": 0.0024071428571428573,
2000
+ "loss": 6.7925,
2001
+ "step": 332
2002
+ },
2003
+ {
2004
+ "epoch": 9.51,
2005
+ "learning_rate": 0.002405357142857143,
2006
+ "loss": 6.7289,
2007
+ "step": 333
2008
+ },
2009
+ {
2010
+ "epoch": 9.54,
2011
+ "learning_rate": 0.0024035714285714285,
2012
+ "loss": 6.7439,
2013
+ "step": 334
2014
+ },
2015
+ {
2016
+ "epoch": 9.57,
2017
+ "learning_rate": 0.0024017857142857144,
2018
+ "loss": 6.7119,
2019
+ "step": 335
2020
+ },
2021
+ {
2022
+ "epoch": 9.6,
2023
+ "learning_rate": 0.0024000000000000002,
2024
+ "loss": 6.7251,
2025
+ "step": 336
2026
+ },
2027
+ {
2028
+ "epoch": 9.63,
2029
+ "learning_rate": 0.002398214285714286,
2030
+ "loss": 6.6659,
2031
+ "step": 337
2032
+ },
2033
+ {
2034
+ "epoch": 9.66,
2035
+ "learning_rate": 0.0023964285714285715,
2036
+ "loss": 6.7422,
2037
+ "step": 338
2038
+ },
2039
+ {
2040
+ "epoch": 9.69,
2041
+ "learning_rate": 0.0023946428571428573,
2042
+ "loss": 6.7852,
2043
+ "step": 339
2044
+ },
2045
+ {
2046
+ "epoch": 9.71,
2047
+ "learning_rate": 0.002392857142857143,
2048
+ "loss": 6.6828,
2049
+ "step": 340
2050
+ },
2051
+ {
2052
+ "epoch": 9.74,
2053
+ "learning_rate": 0.0023910714285714286,
2054
+ "loss": 6.686,
2055
+ "step": 341
2056
+ },
2057
+ {
2058
+ "epoch": 9.77,
2059
+ "learning_rate": 0.002389285714285714,
2060
+ "loss": 6.7326,
2061
+ "step": 342
2062
+ },
2063
+ {
2064
+ "epoch": 9.8,
2065
+ "learning_rate": 0.0023875,
2066
+ "loss": 6.5601,
2067
+ "step": 343
2068
+ },
2069
+ {
2070
+ "epoch": 9.83,
2071
+ "learning_rate": 0.0023857142857142857,
2072
+ "loss": 6.6646,
2073
+ "step": 344
2074
+ },
2075
+ {
2076
+ "epoch": 9.86,
2077
+ "learning_rate": 0.002383928571428571,
2078
+ "loss": 6.5673,
2079
+ "step": 345
2080
+ },
2081
+ {
2082
+ "epoch": 9.89,
2083
+ "learning_rate": 0.002382142857142857,
2084
+ "loss": 6.6227,
2085
+ "step": 346
2086
+ },
2087
+ {
2088
+ "epoch": 9.91,
2089
+ "learning_rate": 0.002380357142857143,
2090
+ "loss": 6.5526,
2091
+ "step": 347
2092
+ },
2093
+ {
2094
+ "epoch": 9.94,
2095
+ "learning_rate": 0.0023785714285714287,
2096
+ "loss": 6.6842,
2097
+ "step": 348
2098
+ },
2099
+ {
2100
+ "epoch": 9.97,
2101
+ "learning_rate": 0.002376785714285714,
2102
+ "loss": 6.6211,
2103
+ "step": 349
2104
+ },
2105
+ {
2106
+ "epoch": 10.0,
2107
+ "learning_rate": 0.002375,
2108
+ "loss": 6.6952,
2109
+ "step": 350
2110
+ },
2111
+ {
2112
+ "epoch": 10.03,
2113
+ "learning_rate": 0.002373214285714286,
2114
+ "loss": 6.5324,
2115
+ "step": 351
2116
+ },
2117
+ {
2118
+ "epoch": 10.06,
2119
+ "learning_rate": 0.002371428571428571,
2120
+ "loss": 6.5792,
2121
+ "step": 352
2122
+ },
2123
+ {
2124
+ "epoch": 10.09,
2125
+ "learning_rate": 0.002369642857142857,
2126
+ "loss": 6.5276,
2127
+ "step": 353
2128
+ },
2129
+ {
2130
+ "epoch": 10.11,
2131
+ "learning_rate": 0.002367857142857143,
2132
+ "loss": 6.5634,
2133
+ "step": 354
2134
+ },
2135
+ {
2136
+ "epoch": 10.14,
2137
+ "learning_rate": 0.0023660714285714288,
2138
+ "loss": 6.5385,
2139
+ "step": 355
2140
+ },
2141
+ {
2142
+ "epoch": 10.17,
2143
+ "learning_rate": 0.002364285714285714,
2144
+ "loss": 6.4516,
2145
+ "step": 356
2146
+ },
2147
+ {
2148
+ "epoch": 10.2,
2149
+ "learning_rate": 0.0023625,
2150
+ "loss": 6.5641,
2151
+ "step": 357
2152
+ },
2153
+ {
2154
+ "epoch": 10.23,
2155
+ "learning_rate": 0.002360714285714286,
2156
+ "loss": 6.5001,
2157
+ "step": 358
2158
+ },
2159
+ {
2160
+ "epoch": 10.26,
2161
+ "learning_rate": 0.0023589285714285713,
2162
+ "loss": 6.4846,
2163
+ "step": 359
2164
+ },
2165
+ {
2166
+ "epoch": 10.29,
2167
+ "learning_rate": 0.002357142857142857,
2168
+ "loss": 6.4638,
2169
+ "step": 360
2170
+ },
2171
+ {
2172
+ "epoch": 10.31,
2173
+ "learning_rate": 0.002355357142857143,
2174
+ "loss": 6.5217,
2175
+ "step": 361
2176
+ },
2177
+ {
2178
+ "epoch": 10.34,
2179
+ "learning_rate": 0.0023535714285714284,
2180
+ "loss": 6.5444,
2181
+ "step": 362
2182
+ },
2183
+ {
2184
+ "epoch": 10.37,
2185
+ "learning_rate": 0.0023517857142857142,
2186
+ "loss": 6.496,
2187
+ "step": 363
2188
+ },
2189
+ {
2190
+ "epoch": 10.4,
2191
+ "learning_rate": 0.00235,
2192
+ "loss": 6.5345,
2193
+ "step": 364
2194
+ },
2195
+ {
2196
+ "epoch": 10.43,
2197
+ "learning_rate": 0.002348214285714286,
2198
+ "loss": 6.4732,
2199
+ "step": 365
2200
+ },
2201
+ {
2202
+ "epoch": 10.46,
2203
+ "learning_rate": 0.0023464285714285714,
2204
+ "loss": 6.4765,
2205
+ "step": 366
2206
+ },
2207
+ {
2208
+ "epoch": 10.49,
2209
+ "learning_rate": 0.002344642857142857,
2210
+ "loss": 6.3881,
2211
+ "step": 367
2212
+ },
2213
+ {
2214
+ "epoch": 10.51,
2215
+ "learning_rate": 0.002342857142857143,
2216
+ "loss": 6.4908,
2217
+ "step": 368
2218
+ },
2219
+ {
2220
+ "epoch": 10.54,
2221
+ "learning_rate": 0.0023410714285714285,
2222
+ "loss": 6.4593,
2223
+ "step": 369
2224
+ },
2225
+ {
2226
+ "epoch": 10.57,
2227
+ "learning_rate": 0.0023392857142857143,
2228
+ "loss": 6.5006,
2229
+ "step": 370
2230
+ },
2231
+ {
2232
+ "epoch": 10.6,
2233
+ "learning_rate": 0.0023375,
2234
+ "loss": 6.4495,
2235
+ "step": 371
2236
+ },
2237
+ {
2238
+ "epoch": 10.63,
2239
+ "learning_rate": 0.0023357142857142856,
2240
+ "loss": 6.3569,
2241
+ "step": 372
2242
+ },
2243
+ {
2244
+ "epoch": 10.66,
2245
+ "learning_rate": 0.0023339285714285714,
2246
+ "loss": 6.3592,
2247
+ "step": 373
2248
+ },
2249
+ {
2250
+ "epoch": 10.69,
2251
+ "learning_rate": 0.0023321428571428573,
2252
+ "loss": 6.3258,
2253
+ "step": 374
2254
+ },
2255
+ {
2256
+ "epoch": 10.71,
2257
+ "learning_rate": 0.002330357142857143,
2258
+ "loss": 6.3216,
2259
+ "step": 375
2260
+ },
2261
+ {
2262
+ "epoch": 10.74,
2263
+ "learning_rate": 0.0023285714285714285,
2264
+ "loss": 6.4878,
2265
+ "step": 376
2266
+ },
2267
+ {
2268
+ "epoch": 10.77,
2269
+ "learning_rate": 0.0023267857142857144,
2270
+ "loss": 6.3412,
2271
+ "step": 377
2272
+ },
2273
+ {
2274
+ "epoch": 10.8,
2275
+ "learning_rate": 0.0023250000000000002,
2276
+ "loss": 6.3925,
2277
+ "step": 378
2278
+ },
2279
+ {
2280
+ "epoch": 10.83,
2281
+ "learning_rate": 0.0023232142857142857,
2282
+ "loss": 6.275,
2283
+ "step": 379
2284
+ },
2285
+ {
2286
+ "epoch": 10.86,
2287
+ "learning_rate": 0.0023214285714285715,
2288
+ "loss": 6.3575,
2289
+ "step": 380
2290
+ },
2291
+ {
2292
+ "epoch": 10.89,
2293
+ "learning_rate": 0.0023196428571428574,
2294
+ "loss": 6.3259,
2295
+ "step": 381
2296
+ },
2297
+ {
2298
+ "epoch": 10.91,
2299
+ "learning_rate": 0.002317857142857143,
2300
+ "loss": 6.315,
2301
+ "step": 382
2302
+ },
2303
+ {
2304
+ "epoch": 10.94,
2305
+ "learning_rate": 0.0023160714285714286,
2306
+ "loss": 6.277,
2307
+ "step": 383
2308
+ },
2309
+ {
2310
+ "epoch": 10.97,
2311
+ "learning_rate": 0.0023142857142857145,
2312
+ "loss": 6.3259,
2313
+ "step": 384
2314
+ },
2315
+ {
2316
+ "epoch": 11.0,
2317
+ "learning_rate": 0.0023125000000000003,
2318
+ "loss": 6.3747,
2319
+ "step": 385
2320
+ },
2321
+ {
2322
+ "epoch": 11.03,
2323
+ "learning_rate": 0.0023107142857142857,
2324
+ "loss": 6.3646,
2325
+ "step": 386
2326
+ },
2327
+ {
2328
+ "epoch": 11.06,
2329
+ "learning_rate": 0.0023089285714285716,
2330
+ "loss": 6.3687,
2331
+ "step": 387
2332
+ },
2333
+ {
2334
+ "epoch": 11.09,
2335
+ "learning_rate": 0.0023071428571428574,
2336
+ "loss": 6.3374,
2337
+ "step": 388
2338
+ },
2339
+ {
2340
+ "epoch": 11.11,
2341
+ "learning_rate": 0.002305357142857143,
2342
+ "loss": 6.3129,
2343
+ "step": 389
2344
+ },
2345
+ {
2346
+ "epoch": 11.14,
2347
+ "learning_rate": 0.0023035714285714287,
2348
+ "loss": 6.3425,
2349
+ "step": 390
2350
+ },
2351
+ {
2352
+ "epoch": 11.17,
2353
+ "learning_rate": 0.0023017857142857145,
2354
+ "loss": 6.2122,
2355
+ "step": 391
2356
+ },
2357
+ {
2358
+ "epoch": 11.2,
2359
+ "learning_rate": 0.0023000000000000004,
2360
+ "loss": 6.2768,
2361
+ "step": 392
2362
+ },
2363
+ {
2364
+ "epoch": 11.23,
2365
+ "learning_rate": 0.002298214285714286,
2366
+ "loss": 6.2853,
2367
+ "step": 393
2368
+ },
2369
+ {
2370
+ "epoch": 11.26,
2371
+ "learning_rate": 0.0022964285714285712,
2372
+ "loss": 6.3215,
2373
+ "step": 394
2374
+ },
2375
+ {
2376
+ "epoch": 11.29,
2377
+ "learning_rate": 0.002294642857142857,
2378
+ "loss": 6.3244,
2379
+ "step": 395
2380
+ },
2381
+ {
2382
+ "epoch": 11.31,
2383
+ "learning_rate": 0.002292857142857143,
2384
+ "loss": 6.2399,
2385
+ "step": 396
2386
+ },
2387
+ {
2388
+ "epoch": 11.34,
2389
+ "learning_rate": 0.0022910714285714283,
2390
+ "loss": 6.2457,
2391
+ "step": 397
2392
+ },
2393
+ {
2394
+ "epoch": 11.37,
2395
+ "learning_rate": 0.002289285714285714,
2396
+ "loss": 6.2018,
2397
+ "step": 398
2398
+ },
2399
+ {
2400
+ "epoch": 11.4,
2401
+ "learning_rate": 0.0022875,
2402
+ "loss": 6.2101,
2403
+ "step": 399
2404
+ },
2405
+ {
2406
+ "epoch": 11.43,
2407
+ "learning_rate": 0.0022857142857142855,
2408
+ "loss": 6.2257,
2409
+ "step": 400
2410
+ },
2411
+ {
2412
+ "epoch": 11.46,
2413
+ "learning_rate": 0.0022839285714285713,
2414
+ "loss": 6.3029,
2415
+ "step": 401
2416
+ },
2417
+ {
2418
+ "epoch": 11.49,
2419
+ "learning_rate": 0.002282142857142857,
2420
+ "loss": 6.2312,
2421
+ "step": 402
2422
+ },
2423
+ {
2424
+ "epoch": 11.51,
2425
+ "learning_rate": 0.002280357142857143,
2426
+ "loss": 6.203,
2427
+ "step": 403
2428
+ },
2429
+ {
2430
+ "epoch": 11.54,
2431
+ "learning_rate": 0.0022785714285714284,
2432
+ "loss": 6.2881,
2433
+ "step": 404
2434
+ },
2435
+ {
2436
+ "epoch": 11.57,
2437
+ "learning_rate": 0.0022767857142857143,
2438
+ "loss": 6.3466,
2439
+ "step": 405
2440
+ },
2441
+ {
2442
+ "epoch": 11.6,
2443
+ "learning_rate": 0.002275,
2444
+ "loss": 6.1908,
2445
+ "step": 406
2446
+ },
2447
+ {
2448
+ "epoch": 11.63,
2449
+ "learning_rate": 0.0022732142857142855,
2450
+ "loss": 6.196,
2451
+ "step": 407
2452
+ },
2453
+ {
2454
+ "epoch": 11.66,
2455
+ "learning_rate": 0.0022714285714285714,
2456
+ "loss": 6.1726,
2457
+ "step": 408
2458
+ },
2459
+ {
2460
+ "epoch": 11.69,
2461
+ "learning_rate": 0.0022696428571428572,
2462
+ "loss": 6.1207,
2463
+ "step": 409
2464
+ },
2465
+ {
2466
+ "epoch": 11.71,
2467
+ "learning_rate": 0.0022678571428571426,
2468
+ "loss": 6.2382,
2469
+ "step": 410
2470
+ },
2471
+ {
2472
+ "epoch": 11.74,
2473
+ "learning_rate": 0.0022660714285714285,
2474
+ "loss": 6.1757,
2475
+ "step": 411
2476
+ },
2477
+ {
2478
+ "epoch": 11.77,
2479
+ "learning_rate": 0.0022642857142857143,
2480
+ "loss": 6.1153,
2481
+ "step": 412
2482
+ },
2483
+ {
2484
+ "epoch": 11.8,
2485
+ "learning_rate": 0.0022625,
2486
+ "loss": 6.1261,
2487
+ "step": 413
2488
+ },
2489
+ {
2490
+ "epoch": 11.83,
2491
+ "learning_rate": 0.0022607142857142856,
2492
+ "loss": 6.0762,
2493
+ "step": 414
2494
+ },
2495
+ {
2496
+ "epoch": 11.86,
2497
+ "learning_rate": 0.0022589285714285715,
2498
+ "loss": 6.1386,
2499
+ "step": 415
2500
+ },
2501
+ {
2502
+ "epoch": 11.89,
2503
+ "learning_rate": 0.0022571428571428573,
2504
+ "loss": 6.1204,
2505
+ "step": 416
2506
+ },
2507
+ {
2508
+ "epoch": 11.91,
2509
+ "learning_rate": 0.0022553571428571427,
2510
+ "loss": 6.1059,
2511
+ "step": 417
2512
+ },
2513
+ {
2514
+ "epoch": 11.94,
2515
+ "learning_rate": 0.0022535714285714286,
2516
+ "loss": 6.0591,
2517
+ "step": 418
2518
+ },
2519
+ {
2520
+ "epoch": 11.97,
2521
+ "learning_rate": 0.0022517857142857144,
2522
+ "loss": 6.1713,
2523
+ "step": 419
2524
+ },
2525
+ {
2526
+ "epoch": 12.0,
2527
+ "learning_rate": 0.0022500000000000003,
2528
+ "loss": 6.2039,
2529
+ "step": 420
2530
+ },
2531
+ {
2532
+ "epoch": 12.03,
2533
+ "learning_rate": 0.0022482142857142857,
2534
+ "loss": 6.0168,
2535
+ "step": 421
2536
+ },
2537
+ {
2538
+ "epoch": 12.06,
2539
+ "learning_rate": 0.0022464285714285715,
2540
+ "loss": 6.0206,
2541
+ "step": 422
2542
+ },
2543
+ {
2544
+ "epoch": 12.09,
2545
+ "learning_rate": 0.0022446428571428574,
2546
+ "loss": 6.0642,
2547
+ "step": 423
2548
+ },
2549
+ {
2550
+ "epoch": 12.11,
2551
+ "learning_rate": 0.002242857142857143,
2552
+ "loss": 6.0665,
2553
+ "step": 424
2554
+ },
2555
+ {
2556
+ "epoch": 12.14,
2557
+ "learning_rate": 0.0022410714285714286,
2558
+ "loss": 5.9766,
2559
+ "step": 425
2560
+ },
2561
+ {
2562
+ "epoch": 12.17,
2563
+ "learning_rate": 0.0022392857142857145,
2564
+ "loss": 6.2167,
2565
+ "step": 426
2566
+ },
2567
+ {
2568
+ "epoch": 12.2,
2569
+ "learning_rate": 0.0022375,
2570
+ "loss": 6.002,
2571
+ "step": 427
2572
+ },
2573
+ {
2574
+ "epoch": 12.23,
2575
+ "learning_rate": 0.0022357142857142858,
2576
+ "loss": 6.0266,
2577
+ "step": 428
2578
+ },
2579
+ {
2580
+ "epoch": 12.26,
2581
+ "learning_rate": 0.0022339285714285716,
2582
+ "loss": 5.9339,
2583
+ "step": 429
2584
+ },
2585
+ {
2586
+ "epoch": 12.29,
2587
+ "learning_rate": 0.0022321428571428575,
2588
+ "loss": 6.1066,
2589
+ "step": 430
2590
+ },
2591
+ {
2592
+ "epoch": 12.31,
2593
+ "learning_rate": 0.002230357142857143,
2594
+ "loss": 5.9262,
2595
+ "step": 431
2596
+ },
2597
+ {
2598
+ "epoch": 12.34,
2599
+ "learning_rate": 0.0022285714285714287,
2600
+ "loss": 6.0696,
2601
+ "step": 432
2602
+ },
2603
+ {
2604
+ "epoch": 12.37,
2605
+ "learning_rate": 0.0022267857142857146,
2606
+ "loss": 5.9181,
2607
+ "step": 433
2608
+ },
2609
+ {
2610
+ "epoch": 12.4,
2611
+ "learning_rate": 0.002225,
2612
+ "loss": 6.0291,
2613
+ "step": 434
2614
+ },
2615
+ {
2616
+ "epoch": 12.43,
2617
+ "learning_rate": 0.002223214285714286,
2618
+ "loss": 5.9493,
2619
+ "step": 435
2620
+ },
2621
+ {
2622
+ "epoch": 12.46,
2623
+ "learning_rate": 0.0022214285714285717,
2624
+ "loss": 5.9639,
2625
+ "step": 436
2626
+ },
2627
+ {
2628
+ "epoch": 12.49,
2629
+ "learning_rate": 0.002219642857142857,
2630
+ "loss": 6.0303,
2631
+ "step": 437
2632
+ },
2633
+ {
2634
+ "epoch": 12.51,
2635
+ "learning_rate": 0.002217857142857143,
2636
+ "loss": 6.0157,
2637
+ "step": 438
2638
+ },
2639
+ {
2640
+ "epoch": 12.54,
2641
+ "learning_rate": 0.002216071428571429,
2642
+ "loss": 5.9309,
2643
+ "step": 439
2644
+ },
2645
+ {
2646
+ "epoch": 12.57,
2647
+ "learning_rate": 0.0022142857142857146,
2648
+ "loss": 5.9554,
2649
+ "step": 440
2650
+ },
2651
+ {
2652
+ "epoch": 12.6,
2653
+ "learning_rate": 0.0022125,
2654
+ "loss": 5.9761,
2655
+ "step": 441
2656
+ },
2657
+ {
2658
+ "epoch": 12.63,
2659
+ "learning_rate": 0.002210714285714286,
2660
+ "loss": 5.9042,
2661
+ "step": 442
2662
+ },
2663
+ {
2664
+ "epoch": 12.66,
2665
+ "learning_rate": 0.0022089285714285718,
2666
+ "loss": 6.0009,
2667
+ "step": 443
2668
+ },
2669
+ {
2670
+ "epoch": 12.69,
2671
+ "learning_rate": 0.002207142857142857,
2672
+ "loss": 5.9199,
2673
+ "step": 444
2674
+ },
2675
+ {
2676
+ "epoch": 12.71,
2677
+ "learning_rate": 0.002205357142857143,
2678
+ "loss": 5.9472,
2679
+ "step": 445
2680
+ },
2681
+ {
2682
+ "epoch": 12.74,
2683
+ "learning_rate": 0.002203571428571429,
2684
+ "loss": 6.0478,
2685
+ "step": 446
2686
+ },
2687
+ {
2688
+ "epoch": 12.77,
2689
+ "learning_rate": 0.0022017857142857143,
2690
+ "loss": 6.0131,
2691
+ "step": 447
2692
+ },
2693
+ {
2694
+ "epoch": 12.8,
2695
+ "learning_rate": 0.0021999999999999997,
2696
+ "loss": 5.9161,
2697
+ "step": 448
2698
+ },
2699
+ {
2700
+ "epoch": 12.83,
2701
+ "learning_rate": 0.0021982142857142855,
2702
+ "loss": 5.935,
2703
+ "step": 449
2704
+ },
2705
+ {
2706
+ "epoch": 12.86,
2707
+ "learning_rate": 0.0021964285714285714,
2708
+ "loss": 5.9035,
2709
+ "step": 450
2710
+ },
2711
+ {
2712
+ "epoch": 12.89,
2713
+ "learning_rate": 0.0021946428571428572,
2714
+ "loss": 5.9422,
2715
+ "step": 451
2716
+ },
2717
+ {
2718
+ "epoch": 12.91,
2719
+ "learning_rate": 0.0021928571428571427,
2720
+ "loss": 6.0135,
2721
+ "step": 452
2722
+ },
2723
+ {
2724
+ "epoch": 12.94,
2725
+ "learning_rate": 0.0021910714285714285,
2726
+ "loss": 5.9757,
2727
+ "step": 453
2728
+ },
2729
+ {
2730
+ "epoch": 12.97,
2731
+ "learning_rate": 0.0021892857142857144,
2732
+ "loss": 5.942,
2733
+ "step": 454
2734
+ },
2735
+ {
2736
+ "epoch": 13.0,
2737
+ "learning_rate": 0.0021874999999999998,
2738
+ "loss": 5.943,
2739
+ "step": 455
2740
+ },
2741
+ {
2742
+ "epoch": 13.03,
2743
+ "learning_rate": 0.0021857142857142856,
2744
+ "loss": 5.8982,
2745
+ "step": 456
2746
+ },
2747
+ {
2748
+ "epoch": 13.06,
2749
+ "learning_rate": 0.0021839285714285715,
2750
+ "loss": 5.9874,
2751
+ "step": 457
2752
+ },
2753
+ {
2754
+ "epoch": 13.09,
2755
+ "learning_rate": 0.002182142857142857,
2756
+ "loss": 5.8677,
2757
+ "step": 458
2758
+ },
2759
+ {
2760
+ "epoch": 13.11,
2761
+ "learning_rate": 0.0021803571428571427,
2762
+ "loss": 5.8782,
2763
+ "step": 459
2764
+ },
2765
+ {
2766
+ "epoch": 13.14,
2767
+ "learning_rate": 0.0021785714285714286,
2768
+ "loss": 5.787,
2769
+ "step": 460
2770
+ },
2771
+ {
2772
+ "epoch": 13.17,
2773
+ "learning_rate": 0.0021767857142857144,
2774
+ "loss": 5.8339,
2775
+ "step": 461
2776
+ },
2777
+ {
2778
+ "epoch": 13.2,
2779
+ "learning_rate": 0.002175,
2780
+ "loss": 5.8303,
2781
+ "step": 462
2782
+ },
2783
+ {
2784
+ "epoch": 13.23,
2785
+ "learning_rate": 0.0021732142857142857,
2786
+ "loss": 5.8187,
2787
+ "step": 463
2788
+ },
2789
+ {
2790
+ "epoch": 13.26,
2791
+ "learning_rate": 0.0021714285714285715,
2792
+ "loss": 5.7448,
2793
+ "step": 464
2794
+ },
2795
+ {
2796
+ "epoch": 13.29,
2797
+ "learning_rate": 0.002169642857142857,
2798
+ "loss": 5.8681,
2799
+ "step": 465
2800
+ },
2801
+ {
2802
+ "epoch": 13.31,
2803
+ "learning_rate": 0.002167857142857143,
2804
+ "loss": 5.8039,
2805
+ "step": 466
2806
+ },
2807
+ {
2808
+ "epoch": 13.34,
2809
+ "learning_rate": 0.0021660714285714287,
2810
+ "loss": 5.8511,
2811
+ "step": 467
2812
+ },
2813
+ {
2814
+ "epoch": 13.37,
2815
+ "learning_rate": 0.0021642857142857145,
2816
+ "loss": 5.8184,
2817
+ "step": 468
2818
+ },
2819
+ {
2820
+ "epoch": 13.4,
2821
+ "learning_rate": 0.0021625,
2822
+ "loss": 5.7656,
2823
+ "step": 469
2824
+ },
2825
+ {
2826
+ "epoch": 13.43,
2827
+ "learning_rate": 0.0021607142857142858,
2828
+ "loss": 5.8613,
2829
+ "step": 470
2830
+ },
2831
+ {
2832
+ "epoch": 13.46,
2833
+ "learning_rate": 0.0021589285714285716,
2834
+ "loss": 5.849,
2835
+ "step": 471
2836
+ },
2837
+ {
2838
+ "epoch": 13.49,
2839
+ "learning_rate": 0.002157142857142857,
2840
+ "loss": 5.8011,
2841
+ "step": 472
2842
+ },
2843
+ {
2844
+ "epoch": 13.51,
2845
+ "learning_rate": 0.002155357142857143,
2846
+ "loss": 5.7813,
2847
+ "step": 473
2848
+ },
2849
+ {
2850
+ "epoch": 13.54,
2851
+ "learning_rate": 0.0021535714285714287,
2852
+ "loss": 5.8186,
2853
+ "step": 474
2854
+ },
2855
+ {
2856
+ "epoch": 13.57,
2857
+ "learning_rate": 0.002151785714285714,
2858
+ "loss": 5.8303,
2859
+ "step": 475
2860
+ },
2861
+ {
2862
+ "epoch": 13.6,
2863
+ "learning_rate": 0.00215,
2864
+ "loss": 5.7879,
2865
+ "step": 476
2866
+ },
2867
+ {
2868
+ "epoch": 13.63,
2869
+ "learning_rate": 0.002148214285714286,
2870
+ "loss": 5.6829,
2871
+ "step": 477
2872
+ },
2873
+ {
2874
+ "epoch": 13.66,
2875
+ "learning_rate": 0.0021464285714285717,
2876
+ "loss": 5.7869,
2877
+ "step": 478
2878
+ },
2879
+ {
2880
+ "epoch": 13.69,
2881
+ "learning_rate": 0.002144642857142857,
2882
+ "loss": 5.6489,
2883
+ "step": 479
2884
+ },
2885
+ {
2886
+ "epoch": 13.71,
2887
+ "learning_rate": 0.002142857142857143,
2888
+ "loss": 5.8708,
2889
+ "step": 480
2890
+ },
2891
+ {
2892
+ "epoch": 13.74,
2893
+ "learning_rate": 0.002141071428571429,
2894
+ "loss": 5.7791,
2895
+ "step": 481
2896
+ },
2897
+ {
2898
+ "epoch": 13.77,
2899
+ "learning_rate": 0.0021392857142857142,
2900
+ "loss": 5.7497,
2901
+ "step": 482
2902
+ },
2903
+ {
2904
+ "epoch": 13.8,
2905
+ "learning_rate": 0.0021375,
2906
+ "loss": 5.827,
2907
+ "step": 483
2908
+ },
2909
+ {
2910
+ "epoch": 13.83,
2911
+ "learning_rate": 0.002135714285714286,
2912
+ "loss": 5.7286,
2913
+ "step": 484
2914
+ },
2915
+ {
2916
+ "epoch": 13.86,
2917
+ "learning_rate": 0.0021339285714285713,
2918
+ "loss": 5.8183,
2919
+ "step": 485
2920
+ },
2921
+ {
2922
+ "epoch": 13.89,
2923
+ "learning_rate": 0.002132142857142857,
2924
+ "loss": 5.7191,
2925
+ "step": 486
2926
+ },
2927
+ {
2928
+ "epoch": 13.91,
2929
+ "learning_rate": 0.002130357142857143,
2930
+ "loss": 5.7647,
2931
+ "step": 487
2932
+ },
2933
+ {
2934
+ "epoch": 13.94,
2935
+ "learning_rate": 0.002128571428571429,
2936
+ "loss": 5.799,
2937
+ "step": 488
2938
+ },
2939
+ {
2940
+ "epoch": 13.97,
2941
+ "learning_rate": 0.0021267857142857143,
2942
+ "loss": 5.7583,
2943
+ "step": 489
2944
+ },
2945
+ {
2946
+ "epoch": 14.0,
2947
+ "learning_rate": 0.002125,
2948
+ "loss": 5.6326,
2949
+ "step": 490
2950
+ },
2951
+ {
2952
+ "epoch": 14.03,
2953
+ "learning_rate": 0.002123214285714286,
2954
+ "loss": 5.614,
2955
+ "step": 491
2956
+ },
2957
+ {
2958
+ "epoch": 14.06,
2959
+ "learning_rate": 0.0021214285714285714,
2960
+ "loss": 5.7278,
2961
+ "step": 492
2962
+ },
2963
+ {
2964
+ "epoch": 14.09,
2965
+ "learning_rate": 0.0021196428571428573,
2966
+ "loss": 5.6661,
2967
+ "step": 493
2968
+ },
2969
+ {
2970
+ "epoch": 14.11,
2971
+ "learning_rate": 0.002117857142857143,
2972
+ "loss": 5.6822,
2973
+ "step": 494
2974
+ },
2975
+ {
2976
+ "epoch": 14.14,
2977
+ "learning_rate": 0.002116071428571429,
2978
+ "loss": 5.7356,
2979
+ "step": 495
2980
+ },
2981
+ {
2982
+ "epoch": 14.17,
2983
+ "learning_rate": 0.0021142857142857144,
2984
+ "loss": 5.6169,
2985
+ "step": 496
2986
+ },
2987
+ {
2988
+ "epoch": 14.2,
2989
+ "learning_rate": 0.0021125000000000002,
2990
+ "loss": 5.7203,
2991
+ "step": 497
2992
+ },
2993
+ {
2994
+ "epoch": 14.23,
2995
+ "learning_rate": 0.002110714285714286,
2996
+ "loss": 5.6377,
2997
+ "step": 498
2998
+ },
2999
+ {
3000
+ "epoch": 14.26,
3001
+ "learning_rate": 0.0021089285714285715,
3002
+ "loss": 5.6836,
3003
+ "step": 499
3004
+ },
3005
+ {
3006
+ "epoch": 14.29,
3007
+ "learning_rate": 0.002107142857142857,
3008
+ "loss": 5.6531,
3009
+ "step": 500
3010
  }
3011
  ],
3012
  "logging_steps": 1,
3013
  "max_steps": 1680,
3014
  "num_train_epochs": 48,
3015
  "save_steps": 100,
3016
+ "total_flos": 2.884638740186112e+17,
3017
  "trial_name": null,
3018
  "trial_params": null
3019
  }