fats-fme commited on
Commit
5cf9d74
1 Parent(s): 8d5f74d

Training in progress, step 331, checkpoint

Browse files
last-checkpoint/adapter_model.safetensors CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:12fef18f99c9bf3ec9eedf986ccbe12d2b84ec11b66e3b9788ae7ec43065b3d7
3
  size 216151256
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:c711b3acc1fea30ace0792a8647c1eb28ba9e50b40350c7bef3281cf3f8bed89
3
  size 216151256
last-checkpoint/optimizer.pt CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:541a7b0bf8fbbc06854b3c570354a27505018117b0f0d67f11955711b3bef1b4
3
  size 432640054
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:d5ac0485e5a8f6b75cf7f0d176f54f2a4035594a63b26a4da5ffe96baa14247e
3
  size 432640054
last-checkpoint/rng_state_0.pth CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:341f7be18cc89c2ad2dec55ac567729ae8e5db65bdf39a5bc196fbd79e2cbf16
3
  size 14512
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:7ecff436e28cf8b97ff38cd7702576b227782a37573ce447ad741d205e3b2d39
3
  size 14512
last-checkpoint/rng_state_1.pth CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:d870e1e8472cc5e0d2cb8fe273473f96e2cec9ffdf9fce6a51cdd5b21cd3bae6
3
  size 14512
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:5aa934b067fcd654999fdef3da89e73cbddd46768498a87a42b87973bc1b4d8f
3
  size 14512
last-checkpoint/scheduler.pt CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:3f919157faf64362df2e66ee2a7671eb7f6cf8287caadba981f351111997c856
3
  size 1064
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:ebd4d40cf7272f037a44174d772897d78df17a0f80306b63ac3efa6337f45285
3
  size 1064
last-checkpoint/trainer_state.json CHANGED
@@ -1,9 +1,9 @@
1
  {
2
  "best_metric": null,
3
  "best_model_checkpoint": null,
4
- "epoch": 0.7502824858757062,
5
  "eval_steps": 83,
6
- "global_step": 249,
7
  "is_hyper_param_search": false,
8
  "is_local_process_zero": true,
9
  "is_world_process_zero": true,
@@ -1782,6 +1782,580 @@
1782
  "eval_samples_per_second": 6.017,
1783
  "eval_steps_per_second": 1.507,
1784
  "step": 249
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1785
  }
1786
  ],
1787
  "logging_steps": 1,
@@ -1796,12 +2370,12 @@
1796
  "should_evaluate": false,
1797
  "should_log": false,
1798
  "should_save": true,
1799
- "should_training_stop": false
1800
  },
1801
  "attributes": {}
1802
  }
1803
  },
1804
- "total_flos": 8.20318075147518e+17,
1805
  "train_batch_size": 2,
1806
  "trial_name": null,
1807
  "trial_params": null
 
1
  {
2
  "best_metric": null,
3
  "best_model_checkpoint": null,
4
+ "epoch": 0.9973634651600753,
5
  "eval_steps": 83,
6
+ "global_step": 331,
7
  "is_hyper_param_search": false,
8
  "is_local_process_zero": true,
9
  "is_world_process_zero": true,
 
1782
  "eval_samples_per_second": 6.017,
1783
  "eval_steps_per_second": 1.507,
1784
  "step": 249
1785
+ },
1786
+ {
1787
+ "epoch": 0.7532956685499058,
1788
+ "grad_norm": 4.4879302978515625,
1789
+ "learning_rate": 1.9138676015144764e-05,
1790
+ "loss": 0.4317,
1791
+ "step": 250
1792
+ },
1793
+ {
1794
+ "epoch": 0.7563088512241055,
1795
+ "grad_norm": 1.1887656450271606,
1796
+ "learning_rate": 1.870079900469392e-05,
1797
+ "loss": 0.3761,
1798
+ "step": 251
1799
+ },
1800
+ {
1801
+ "epoch": 0.7593220338983051,
1802
+ "grad_norm": 1.1247776746749878,
1803
+ "learning_rate": 1.8266834147258578e-05,
1804
+ "loss": 0.3736,
1805
+ "step": 252
1806
+ },
1807
+ {
1808
+ "epoch": 0.7623352165725047,
1809
+ "grad_norm": 1.001464605331421,
1810
+ "learning_rate": 1.7836835685019733e-05,
1811
+ "loss": 0.3244,
1812
+ "step": 253
1813
+ },
1814
+ {
1815
+ "epoch": 0.7653483992467043,
1816
+ "grad_norm": 0.8156184554100037,
1817
+ "learning_rate": 1.741085736439031e-05,
1818
+ "loss": 0.254,
1819
+ "step": 254
1820
+ },
1821
+ {
1822
+ "epoch": 0.768361581920904,
1823
+ "grad_norm": 0.8647398352622986,
1824
+ "learning_rate": 1.698895242929725e-05,
1825
+ "loss": 0.271,
1826
+ "step": 255
1827
+ },
1828
+ {
1829
+ "epoch": 0.7713747645951036,
1830
+ "grad_norm": 1.146620750427246,
1831
+ "learning_rate": 1.6571173614526507e-05,
1832
+ "loss": 0.3116,
1833
+ "step": 256
1834
+ },
1835
+ {
1836
+ "epoch": 0.7743879472693032,
1837
+ "grad_norm": 0.8247811198234558,
1838
+ "learning_rate": 1.6157573139131527e-05,
1839
+ "loss": 0.231,
1840
+ "step": 257
1841
+ },
1842
+ {
1843
+ "epoch": 0.7774011299435029,
1844
+ "grad_norm": 1.2048598527908325,
1845
+ "learning_rate": 1.5748202699906335e-05,
1846
+ "loss": 0.328,
1847
+ "step": 258
1848
+ },
1849
+ {
1850
+ "epoch": 0.7804143126177024,
1851
+ "grad_norm": 0.8339473009109497,
1852
+ "learning_rate": 1.534311346492381e-05,
1853
+ "loss": 0.2627,
1854
+ "step": 259
1855
+ },
1856
+ {
1857
+ "epoch": 0.783427495291902,
1858
+ "grad_norm": 1.1890642642974854,
1859
+ "learning_rate": 1.4942356067140162e-05,
1860
+ "loss": 0.3058,
1861
+ "step": 260
1862
+ },
1863
+ {
1864
+ "epoch": 0.7864406779661017,
1865
+ "grad_norm": 0.8932839035987854,
1866
+ "learning_rate": 1.454598059806609e-05,
1867
+ "loss": 0.2475,
1868
+ "step": 261
1869
+ },
1870
+ {
1871
+ "epoch": 0.7894538606403013,
1872
+ "grad_norm": 1.4562137126922607,
1873
+ "learning_rate": 1.4154036601505832e-05,
1874
+ "loss": 0.3751,
1875
+ "step": 262
1876
+ },
1877
+ {
1878
+ "epoch": 0.7924670433145009,
1879
+ "grad_norm": 1.0580323934555054,
1880
+ "learning_rate": 1.376657306736453e-05,
1881
+ "loss": 0.2916,
1882
+ "step": 263
1883
+ },
1884
+ {
1885
+ "epoch": 0.7954802259887006,
1886
+ "grad_norm": 0.9510928988456726,
1887
+ "learning_rate": 1.3383638425524908e-05,
1888
+ "loss": 0.2661,
1889
+ "step": 264
1890
+ },
1891
+ {
1892
+ "epoch": 0.7984934086629002,
1893
+ "grad_norm": 0.7758486866950989,
1894
+ "learning_rate": 1.3005280539793907e-05,
1895
+ "loss": 0.2241,
1896
+ "step": 265
1897
+ },
1898
+ {
1899
+ "epoch": 0.8015065913370998,
1900
+ "grad_norm": 1.2630360126495361,
1901
+ "learning_rate": 1.2631546701920071e-05,
1902
+ "loss": 0.2934,
1903
+ "step": 266
1904
+ },
1905
+ {
1906
+ "epoch": 0.8045197740112995,
1907
+ "grad_norm": 0.8792417645454407,
1908
+ "learning_rate": 1.2262483625682513e-05,
1909
+ "loss": 0.2504,
1910
+ "step": 267
1911
+ },
1912
+ {
1913
+ "epoch": 0.8075329566854991,
1914
+ "grad_norm": 1.050751805305481,
1915
+ "learning_rate": 1.1898137441051982e-05,
1916
+ "loss": 0.2669,
1917
+ "step": 268
1918
+ },
1919
+ {
1920
+ "epoch": 0.8105461393596987,
1921
+ "grad_norm": 0.9729787111282349,
1922
+ "learning_rate": 1.1538553688425003e-05,
1923
+ "loss": 0.266,
1924
+ "step": 269
1925
+ },
1926
+ {
1927
+ "epoch": 0.8135593220338984,
1928
+ "grad_norm": 2.0321502685546875,
1929
+ "learning_rate": 1.1183777312931748e-05,
1930
+ "loss": 0.4952,
1931
+ "step": 270
1932
+ },
1933
+ {
1934
+ "epoch": 0.816572504708098,
1935
+ "grad_norm": 1.9791584014892578,
1936
+ "learning_rate": 1.0833852658818166e-05,
1937
+ "loss": 0.4964,
1938
+ "step": 271
1939
+ },
1940
+ {
1941
+ "epoch": 0.8195856873822975,
1942
+ "grad_norm": 1.8695249557495117,
1943
+ "learning_rate": 1.0488823463903342e-05,
1944
+ "loss": 0.4246,
1945
+ "step": 272
1946
+ },
1947
+ {
1948
+ "epoch": 0.8225988700564971,
1949
+ "grad_norm": 1.9649566411972046,
1950
+ "learning_rate": 1.0148732854112619e-05,
1951
+ "loss": 0.3945,
1952
+ "step": 273
1953
+ },
1954
+ {
1955
+ "epoch": 0.8256120527306968,
1956
+ "grad_norm": 2.423754930496216,
1957
+ "learning_rate": 9.81362333808718e-06,
1958
+ "loss": 0.3351,
1959
+ "step": 274
1960
+ },
1961
+ {
1962
+ "epoch": 0.8286252354048964,
1963
+ "grad_norm": 7.4359540939331055,
1964
+ "learning_rate": 9.483536801870834e-06,
1965
+ "loss": 0.7226,
1966
+ "step": 275
1967
+ },
1968
+ {
1969
+ "epoch": 0.831638418079096,
1970
+ "grad_norm": 1.0027852058410645,
1971
+ "learning_rate": 9.158514503674543e-06,
1972
+ "loss": 0.4422,
1973
+ "step": 276
1974
+ },
1975
+ {
1976
+ "epoch": 0.8346516007532957,
1977
+ "grad_norm": 0.9810426235198975,
1978
+ "learning_rate": 8.838597068719518e-06,
1979
+ "loss": 0.4183,
1980
+ "step": 277
1981
+ },
1982
+ {
1983
+ "epoch": 0.8376647834274953,
1984
+ "grad_norm": 0.9647234678268433,
1985
+ "learning_rate": 8.523824484159349e-06,
1986
+ "loss": 0.342,
1987
+ "step": 278
1988
+ },
1989
+ {
1990
+ "epoch": 0.8406779661016949,
1991
+ "grad_norm": 1.0083119869232178,
1992
+ "learning_rate": 8.21423609408199e-06,
1993
+ "loss": 0.3176,
1994
+ "step": 279
1995
+ },
1996
+ {
1997
+ "epoch": 0.8436911487758946,
1998
+ "grad_norm": 1.0560261011123657,
1999
+ "learning_rate": 7.90987059459195e-06,
2000
+ "loss": 0.3063,
2001
+ "step": 280
2002
+ },
2003
+ {
2004
+ "epoch": 0.8467043314500942,
2005
+ "grad_norm": 0.7893863916397095,
2006
+ "learning_rate": 7.610766028973709e-06,
2007
+ "loss": 0.2334,
2008
+ "step": 281
2009
+ },
2010
+ {
2011
+ "epoch": 0.8497175141242937,
2012
+ "grad_norm": 0.8123882412910461,
2013
+ "learning_rate": 7.3169597829365165e-06,
2014
+ "loss": 0.2431,
2015
+ "step": 282
2016
+ },
2017
+ {
2018
+ "epoch": 0.8527306967984934,
2019
+ "grad_norm": 0.7712526917457581,
2020
+ "learning_rate": 7.028488579941506e-06,
2021
+ "loss": 0.2199,
2022
+ "step": 283
2023
+ },
2024
+ {
2025
+ "epoch": 0.855743879472693,
2026
+ "grad_norm": 0.821006715297699,
2027
+ "learning_rate": 6.745388476611553e-06,
2028
+ "loss": 0.2353,
2029
+ "step": 284
2030
+ },
2031
+ {
2032
+ "epoch": 0.8587570621468926,
2033
+ "grad_norm": 1.0905379056930542,
2034
+ "learning_rate": 6.467694858224488e-06,
2035
+ "loss": 0.2829,
2036
+ "step": 285
2037
+ },
2038
+ {
2039
+ "epoch": 0.8617702448210923,
2040
+ "grad_norm": 1.1444308757781982,
2041
+ "learning_rate": 6.1954424342902e-06,
2042
+ "loss": 0.2891,
2043
+ "step": 286
2044
+ },
2045
+ {
2046
+ "epoch": 0.8647834274952919,
2047
+ "grad_norm": 0.8933337926864624,
2048
+ "learning_rate": 5.928665234212233e-06,
2049
+ "loss": 0.2404,
2050
+ "step": 287
2051
+ },
2052
+ {
2053
+ "epoch": 0.8677966101694915,
2054
+ "grad_norm": 1.0412938594818115,
2055
+ "learning_rate": 5.66739660303437e-06,
2056
+ "loss": 0.2752,
2057
+ "step": 288
2058
+ },
2059
+ {
2060
+ "epoch": 0.8708097928436912,
2061
+ "grad_norm": 0.9225270748138428,
2062
+ "learning_rate": 5.411669197272795e-06,
2063
+ "loss": 0.2548,
2064
+ "step": 289
2065
+ },
2066
+ {
2067
+ "epoch": 0.8738229755178908,
2068
+ "grad_norm": 0.8741989731788635,
2069
+ "learning_rate": 5.161514980834231e-06,
2070
+ "loss": 0.2349,
2071
+ "step": 290
2072
+ },
2073
+ {
2074
+ "epoch": 0.8768361581920904,
2075
+ "grad_norm": 0.7688031792640686,
2076
+ "learning_rate": 4.916965221020753e-06,
2077
+ "loss": 0.2232,
2078
+ "step": 291
2079
+ },
2080
+ {
2081
+ "epoch": 0.87984934086629,
2082
+ "grad_norm": 0.9201337099075317,
2083
+ "learning_rate": 4.678050484621615e-06,
2084
+ "loss": 0.2486,
2085
+ "step": 292
2086
+ },
2087
+ {
2088
+ "epoch": 0.8828625235404897,
2089
+ "grad_norm": 0.8050046563148499,
2090
+ "learning_rate": 4.444800634092616e-06,
2091
+ "loss": 0.2339,
2092
+ "step": 293
2093
+ },
2094
+ {
2095
+ "epoch": 0.8858757062146893,
2096
+ "grad_norm": 0.916643500328064,
2097
+ "learning_rate": 4.217244823823546e-06,
2098
+ "loss": 0.2378,
2099
+ "step": 294
2100
+ },
2101
+ {
2102
+ "epoch": 0.8888888888888888,
2103
+ "grad_norm": 1.2140140533447266,
2104
+ "learning_rate": 3.995411496494134e-06,
2105
+ "loss": 0.2966,
2106
+ "step": 295
2107
+ },
2108
+ {
2109
+ "epoch": 0.8919020715630885,
2110
+ "grad_norm": 2.333122730255127,
2111
+ "learning_rate": 3.7793283795188984e-06,
2112
+ "loss": 0.5715,
2113
+ "step": 296
2114
+ },
2115
+ {
2116
+ "epoch": 0.8949152542372881,
2117
+ "grad_norm": 1.4072636365890503,
2118
+ "learning_rate": 3.56902248158148e-06,
2119
+ "loss": 0.3899,
2120
+ "step": 297
2121
+ },
2122
+ {
2123
+ "epoch": 0.8979284369114877,
2124
+ "grad_norm": 1.8280621767044067,
2125
+ "learning_rate": 3.364520089258727e-06,
2126
+ "loss": 0.3525,
2127
+ "step": 298
2128
+ },
2129
+ {
2130
+ "epoch": 0.9009416195856874,
2131
+ "grad_norm": 2.5405969619750977,
2132
+ "learning_rate": 3.165846763735153e-06,
2133
+ "loss": 0.34,
2134
+ "step": 299
2135
+ },
2136
+ {
2137
+ "epoch": 0.903954802259887,
2138
+ "grad_norm": 8.415023803710938,
2139
+ "learning_rate": 2.973027337607892e-06,
2140
+ "loss": 0.6817,
2141
+ "step": 300
2142
+ },
2143
+ {
2144
+ "epoch": 0.9069679849340866,
2145
+ "grad_norm": 1.0418468713760376,
2146
+ "learning_rate": 2.7860859117828987e-06,
2147
+ "loss": 0.4058,
2148
+ "step": 301
2149
+ },
2150
+ {
2151
+ "epoch": 0.9099811676082863,
2152
+ "grad_norm": 0.9007613062858582,
2153
+ "learning_rate": 2.605045852462473e-06,
2154
+ "loss": 0.3921,
2155
+ "step": 302
2156
+ },
2157
+ {
2158
+ "epoch": 0.9129943502824859,
2159
+ "grad_norm": 1.1040724515914917,
2160
+ "learning_rate": 2.429929788224722e-06,
2161
+ "loss": 0.344,
2162
+ "step": 303
2163
+ },
2164
+ {
2165
+ "epoch": 0.9160075329566855,
2166
+ "grad_norm": 0.8270070552825928,
2167
+ "learning_rate": 2.2607596071951286e-06,
2168
+ "loss": 0.2523,
2169
+ "step": 304
2170
+ },
2171
+ {
2172
+ "epoch": 0.9190207156308852,
2173
+ "grad_norm": 1.036444067955017,
2174
+ "learning_rate": 2.097556454310701e-06,
2175
+ "loss": 0.2802,
2176
+ "step": 305
2177
+ },
2178
+ {
2179
+ "epoch": 0.9220338983050848,
2180
+ "grad_norm": 1.1080818176269531,
2181
+ "learning_rate": 1.940340728677059e-06,
2182
+ "loss": 0.2779,
2183
+ "step": 306
2184
+ },
2185
+ {
2186
+ "epoch": 0.9250470809792843,
2187
+ "grad_norm": 0.9475107192993164,
2188
+ "learning_rate": 1.789132081018674e-06,
2189
+ "loss": 0.2591,
2190
+ "step": 307
2191
+ },
2192
+ {
2193
+ "epoch": 0.928060263653484,
2194
+ "grad_norm": 0.7941210269927979,
2195
+ "learning_rate": 1.6439494112227172e-06,
2196
+ "loss": 0.2142,
2197
+ "step": 308
2198
+ },
2199
+ {
2200
+ "epoch": 0.9310734463276836,
2201
+ "grad_norm": 0.8892014622688293,
2202
+ "learning_rate": 1.5048108659766691e-06,
2203
+ "loss": 0.2625,
2204
+ "step": 309
2205
+ },
2206
+ {
2207
+ "epoch": 0.9340866290018832,
2208
+ "grad_norm": 0.9323367476463318,
2209
+ "learning_rate": 1.3717338365001942e-06,
2210
+ "loss": 0.2504,
2211
+ "step": 310
2212
+ },
2213
+ {
2214
+ "epoch": 0.9370998116760829,
2215
+ "grad_norm": 1.1987720727920532,
2216
+ "learning_rate": 1.2447349563713184e-06,
2217
+ "loss": 0.2877,
2218
+ "step": 311
2219
+ },
2220
+ {
2221
+ "epoch": 0.9401129943502825,
2222
+ "grad_norm": 0.9108150005340576,
2223
+ "learning_rate": 1.1238300994473983e-06,
2224
+ "loss": 0.2055,
2225
+ "step": 312
2226
+ },
2227
+ {
2228
+ "epoch": 0.9431261770244821,
2229
+ "grad_norm": 0.8241666555404663,
2230
+ "learning_rate": 1.0090343778809908e-06,
2231
+ "loss": 0.2561,
2232
+ "step": 313
2233
+ },
2234
+ {
2235
+ "epoch": 0.9461393596986817,
2236
+ "grad_norm": 1.0146571397781372,
2237
+ "learning_rate": 9.003621402309814e-07,
2238
+ "loss": 0.271,
2239
+ "step": 314
2240
+ },
2241
+ {
2242
+ "epoch": 0.9491525423728814,
2243
+ "grad_norm": 0.7878392934799194,
2244
+ "learning_rate": 7.97826969669102e-07,
2245
+ "loss": 0.2338,
2246
+ "step": 315
2247
+ },
2248
+ {
2249
+ "epoch": 0.952165725047081,
2250
+ "grad_norm": 1.097957730293274,
2251
+ "learning_rate": 7.014416822821556e-07,
2252
+ "loss": 0.2901,
2253
+ "step": 316
2254
+ },
2255
+ {
2256
+ "epoch": 0.9551789077212806,
2257
+ "grad_norm": 0.8541196584701538,
2258
+ "learning_rate": 6.112183254700865e-07,
2259
+ "loss": 0.2408,
2260
+ "step": 317
2261
+ },
2262
+ {
2263
+ "epoch": 0.9581920903954803,
2264
+ "grad_norm": 0.9861576557159424,
2265
+ "learning_rate": 5.271681764401848e-07,
2266
+ "loss": 0.2545,
2267
+ "step": 318
2268
+ },
2269
+ {
2270
+ "epoch": 0.9612052730696798,
2271
+ "grad_norm": 1.3217852115631104,
2272
+ "learning_rate": 4.493017407975086e-07,
2273
+ "loss": 0.3015,
2274
+ "step": 319
2275
+ },
2276
+ {
2277
+ "epoch": 0.9642184557438794,
2278
+ "grad_norm": 1.4543648958206177,
2279
+ "learning_rate": 3.7762875123173445e-07,
2280
+ "loss": 0.3321,
2281
+ "step": 320
2282
+ },
2283
+ {
2284
+ "epoch": 0.9672316384180791,
2285
+ "grad_norm": 2.7887980937957764,
2286
+ "learning_rate": 3.1215816630071335e-07,
2287
+ "loss": 0.5545,
2288
+ "step": 321
2289
+ },
2290
+ {
2291
+ "epoch": 0.9702448210922787,
2292
+ "grad_norm": 1.5680711269378662,
2293
+ "learning_rate": 2.528981693106558e-07,
2294
+ "loss": 0.4085,
2295
+ "step": 322
2296
+ },
2297
+ {
2298
+ "epoch": 0.9732580037664783,
2299
+ "grad_norm": 2.545147180557251,
2300
+ "learning_rate": 1.9985616729332747e-07,
2301
+ "loss": 0.4379,
2302
+ "step": 323
2303
+ },
2304
+ {
2305
+ "epoch": 0.976271186440678,
2306
+ "grad_norm": 2.684563159942627,
2307
+ "learning_rate": 1.530387900802177e-07,
2308
+ "loss": 0.3865,
2309
+ "step": 324
2310
+ },
2311
+ {
2312
+ "epoch": 0.9792843691148776,
2313
+ "grad_norm": 3.9092459678649902,
2314
+ "learning_rate": 1.1245188947384134e-07,
2315
+ "loss": 0.4588,
2316
+ "step": 325
2317
+ },
2318
+ {
2319
+ "epoch": 0.9822975517890772,
2320
+ "grad_norm": 0.7552906274795532,
2321
+ "learning_rate": 7.81005385163458e-08,
2322
+ "loss": 0.2851,
2323
+ "step": 326
2324
+ },
2325
+ {
2326
+ "epoch": 0.9853107344632769,
2327
+ "grad_norm": 0.8308711051940918,
2328
+ "learning_rate": 4.998903085539075e-08,
2329
+ "loss": 0.251,
2330
+ "step": 327
2331
+ },
2332
+ {
2333
+ "epoch": 0.9883239171374765,
2334
+ "grad_norm": 0.9575715661048889,
2335
+ "learning_rate": 2.8120880207493928e-08,
2336
+ "loss": 0.2713,
2337
+ "step": 328
2338
+ },
2339
+ {
2340
+ "epoch": 0.9913370998116761,
2341
+ "grad_norm": 0.8187337517738342,
2342
+ "learning_rate": 1.2498819918843607e-08,
2343
+ "loss": 0.2334,
2344
+ "step": 329
2345
+ },
2346
+ {
2347
+ "epoch": 0.9943502824858758,
2348
+ "grad_norm": 0.9916722178459167,
2349
+ "learning_rate": 3.1248026236274652e-09,
2350
+ "loss": 0.2765,
2351
+ "step": 330
2352
+ },
2353
+ {
2354
+ "epoch": 0.9973634651600753,
2355
+ "grad_norm": 1.3465464115142822,
2356
+ "learning_rate": 0.0,
2357
+ "loss": 0.3738,
2358
+ "step": 331
2359
  }
2360
  ],
2361
  "logging_steps": 1,
 
2370
  "should_evaluate": false,
2371
  "should_log": false,
2372
  "should_save": true,
2373
+ "should_training_stop": true
2374
  },
2375
  "attributes": {}
2376
  }
2377
  },
2378
+ "total_flos": 1.0904629834290299e+18,
2379
  "train_batch_size": 2,
2380
  "trial_name": null,
2381
  "trial_params": null