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null | transformers |
# MultiBERTs, Intermediate Checkpoint - Seed 1, Step 800k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://github.com/google-research/bert) but
with differen... | {"language": "en", "license": "apache-2.0", "tags": ["multiberts", "multiberts-seed_1", "multiberts-seed_1-step_800k"]} | google/multiberts-seed_1-step_800k | null | [
"transformers",
"pytorch",
"tf",
"bert",
"pretraining",
"multiberts",
"multiberts-seed_1",
"multiberts-seed_1-step_800k",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2106.16163",
"1908.08962"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_1 #multiberts-seed_1-step_800k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us
|
# MultiBERTs, Intermediate Checkpoint - Seed 1, Step 800k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
the original BERT model but
with different random seeds, which causes variations in ... | [
"# MultiBERTs, Intermediate Checkpoint - Seed 1, Step 800k\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT. We provide 25 BERT-base models trained with\nsimilar hyper-parameters as\nthe original BERT model but\nwith different random seeds, which causes vari... | [
"TAGS\n#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_1 #multiberts-seed_1-step_800k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# MultiBERTs, Intermediate Checkpoint - Seed 1, Step 800k\n\nMultiBERTs is a collection of checkpoints... |
null | transformers |
# MultiBERTs, Intermediate Checkpoint - Seed 1, Step 80k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://github.com/google-research/bert) but
with different... | {"language": "en", "license": "apache-2.0", "tags": ["multiberts", "multiberts-seed_1", "multiberts-seed_1-step_80k"]} | google/multiberts-seed_1-step_80k | null | [
"transformers",
"pytorch",
"tf",
"bert",
"pretraining",
"multiberts",
"multiberts-seed_1",
"multiberts-seed_1-step_80k",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2106.16163",
"1908.08962"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_1 #multiberts-seed_1-step_80k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us
|
# MultiBERTs, Intermediate Checkpoint - Seed 1, Step 80k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
the original BERT model but
with different random seeds, which causes variations in t... | [
"# MultiBERTs, Intermediate Checkpoint - Seed 1, Step 80k\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT. We provide 25 BERT-base models trained with\nsimilar hyper-parameters as\nthe original BERT model but\nwith different random seeds, which causes varia... | [
"TAGS\n#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_1 #multiberts-seed_1-step_80k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# MultiBERTs, Intermediate Checkpoint - Seed 1, Step 80k\n\nMultiBERTs is a collection of checkpoints a... |
null | transformers |
# MultiBERTs, Intermediate Checkpoint - Seed 1, Step 900k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://github.com/google-research/bert) but
with differen... | {"language": "en", "license": "apache-2.0", "tags": ["multiberts", "multiberts-seed_1", "multiberts-seed_1-step_900k"]} | google/multiberts-seed_1-step_900k | null | [
"transformers",
"pytorch",
"tf",
"bert",
"pretraining",
"multiberts",
"multiberts-seed_1",
"multiberts-seed_1-step_900k",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2106.16163",
"1908.08962"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_1 #multiberts-seed_1-step_900k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us
|
# MultiBERTs, Intermediate Checkpoint - Seed 1, Step 900k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
the original BERT model but
with different random seeds, which causes variations in ... | [
"# MultiBERTs, Intermediate Checkpoint - Seed 1, Step 900k\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT. We provide 25 BERT-base models trained with\nsimilar hyper-parameters as\nthe original BERT model but\nwith different random seeds, which causes vari... | [
"TAGS\n#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_1 #multiberts-seed_1-step_900k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# MultiBERTs, Intermediate Checkpoint - Seed 1, Step 900k\n\nMultiBERTs is a collection of checkpoints... |
null | transformers |
# MultiBERTs - Seed 1
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://github.com/google-research/bert) but
with different random seeds, which causes variati... | {"language": "en", "license": "apache-2.0", "tags": ["multiberts", "multiberts-seed_1"]} | google/multiberts-seed_1 | null | [
"transformers",
"pytorch",
"tf",
"bert",
"pretraining",
"multiberts",
"multiberts-seed_1",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2106.16163",
"1908.08962"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_1 #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us
|
# MultiBERTs - Seed 1
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
the original BERT model but
with different random seeds, which causes variations in the initial weights and order of
tra... | [
"# MultiBERTs - Seed 1\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT. We provide 25 BERT-base models trained with\nsimilar hyper-parameters as\nthe original BERT model but\nwith different random seeds, which causes variations in the initial weights and or... | [
"TAGS\n#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_1 #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# MultiBERTs - Seed 1\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT. W... |
null | transformers |
# MultiBERTs - Seed 10
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://github.com/google-research/bert) but
with different random seeds, which causes variat... | {"language": "en", "license": "apache-2.0", "tags": ["multiberts", "multiberts-seed_10"]} | google/multiberts-seed_10 | null | [
"transformers",
"pytorch",
"tf",
"bert",
"pretraining",
"multiberts",
"multiberts-seed_10",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2106.16163",
"1908.08962"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_10 #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us
|
# MultiBERTs - Seed 10
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
the original BERT model but
with different random seeds, which causes variations in the initial weights and order of
tr... | [
"# MultiBERTs - Seed 10\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT. We provide 25 BERT-base models trained with\nsimilar hyper-parameters as\nthe original BERT model but\nwith different random seeds, which causes variations in the initial weights and o... | [
"TAGS\n#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_10 #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# MultiBERTs - Seed 10\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT.... |
null | transformers |
# MultiBERTs - Seed 11
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://github.com/google-research/bert) but
with different random seeds, which causes variat... | {"language": "en", "license": "apache-2.0", "tags": ["multiberts", "multiberts-seed_11"]} | google/multiberts-seed_11 | null | [
"transformers",
"pytorch",
"tf",
"bert",
"pretraining",
"multiberts",
"multiberts-seed_11",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2106.16163",
"1908.08962"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_11 #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us
|
# MultiBERTs - Seed 11
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
the original BERT model but
with different random seeds, which causes variations in the initial weights and order of
tr... | [
"# MultiBERTs - Seed 11\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT. We provide 25 BERT-base models trained with\nsimilar hyper-parameters as\nthe original BERT model but\nwith different random seeds, which causes variations in the initial weights and o... | [
"TAGS\n#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_11 #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# MultiBERTs - Seed 11\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT.... |
null | transformers |
# MultiBERTs - Seed 12
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://github.com/google-research/bert) but
with different random seeds, which causes variat... | {"language": "en", "license": "apache-2.0", "tags": ["multiberts", "multiberts-seed_12"]} | google/multiberts-seed_12 | null | [
"transformers",
"pytorch",
"tf",
"bert",
"pretraining",
"multiberts",
"multiberts-seed_12",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2106.16163",
"1908.08962"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_12 #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us
|
# MultiBERTs - Seed 12
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
the original BERT model but
with different random seeds, which causes variations in the initial weights and order of
tr... | [
"# MultiBERTs - Seed 12\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT. We provide 25 BERT-base models trained with\nsimilar hyper-parameters as\nthe original BERT model but\nwith different random seeds, which causes variations in the initial weights and o... | [
"TAGS\n#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_12 #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# MultiBERTs - Seed 12\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT.... |
null | transformers |
# MultiBERTs - Seed 13
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://github.com/google-research/bert) but
with different random seeds, which causes variat... | {"language": "en", "license": "apache-2.0", "tags": ["multiberts", "multiberts-seed_13"]} | google/multiberts-seed_13 | null | [
"transformers",
"pytorch",
"tf",
"bert",
"pretraining",
"multiberts",
"multiberts-seed_13",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2106.16163",
"1908.08962"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_13 #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us
|
# MultiBERTs - Seed 13
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
the original BERT model but
with different random seeds, which causes variations in the initial weights and order of
tr... | [
"# MultiBERTs - Seed 13\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT. We provide 25 BERT-base models trained with\nsimilar hyper-parameters as\nthe original BERT model but\nwith different random seeds, which causes variations in the initial weights and o... | [
"TAGS\n#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_13 #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# MultiBERTs - Seed 13\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT.... |
null | transformers |
# MultiBERTs - Seed 14
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://github.com/google-research/bert) but
with different random seeds, which causes variat... | {"language": "en", "license": "apache-2.0", "tags": ["multiberts", "multiberts-seed_14"]} | google/multiberts-seed_14 | null | [
"transformers",
"pytorch",
"tf",
"bert",
"pretraining",
"multiberts",
"multiberts-seed_14",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2106.16163",
"1908.08962"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_14 #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us
|
# MultiBERTs - Seed 14
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
the original BERT model but
with different random seeds, which causes variations in the initial weights and order of
tr... | [
"# MultiBERTs - Seed 14\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT. We provide 25 BERT-base models trained with\nsimilar hyper-parameters as\nthe original BERT model but\nwith different random seeds, which causes variations in the initial weights and o... | [
"TAGS\n#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_14 #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# MultiBERTs - Seed 14\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT.... |
null | transformers |
# MultiBERTs - Seed 15
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://github.com/google-research/bert) but
with different random seeds, which causes variat... | {"language": "en", "license": "apache-2.0", "tags": ["multiberts", "multiberts-seed_15"]} | google/multiberts-seed_15 | null | [
"transformers",
"pytorch",
"tf",
"bert",
"pretraining",
"multiberts",
"multiberts-seed_15",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2106.16163",
"1908.08962"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_15 #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us
|
# MultiBERTs - Seed 15
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
the original BERT model but
with different random seeds, which causes variations in the initial weights and order of
tr... | [
"# MultiBERTs - Seed 15\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT. We provide 25 BERT-base models trained with\nsimilar hyper-parameters as\nthe original BERT model but\nwith different random seeds, which causes variations in the initial weights and o... | [
"TAGS\n#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_15 #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# MultiBERTs - Seed 15\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT.... |
null | transformers |
# MultiBERTs - Seed 16
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://github.com/google-research/bert) but
with different random seeds, which causes variat... | {"language": "en", "license": "apache-2.0", "tags": ["multiberts", "multiberts-seed_16"]} | google/multiberts-seed_16 | null | [
"transformers",
"pytorch",
"tf",
"bert",
"pretraining",
"multiberts",
"multiberts-seed_16",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2106.16163",
"1908.08962"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_16 #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us
|
# MultiBERTs - Seed 16
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
the original BERT model but
with different random seeds, which causes variations in the initial weights and order of
tr... | [
"# MultiBERTs - Seed 16\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT. We provide 25 BERT-base models trained with\nsimilar hyper-parameters as\nthe original BERT model but\nwith different random seeds, which causes variations in the initial weights and o... | [
"TAGS\n#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_16 #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# MultiBERTs - Seed 16\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT.... |
null | transformers |
# MultiBERTs - Seed 17
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://github.com/google-research/bert) but
with different random seeds, which causes variat... | {"language": "en", "license": "apache-2.0", "tags": ["multiberts", "multiberts-seed_17"]} | google/multiberts-seed_17 | null | [
"transformers",
"pytorch",
"tf",
"bert",
"pretraining",
"multiberts",
"multiberts-seed_17",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2106.16163",
"1908.08962"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_17 #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us
|
# MultiBERTs - Seed 17
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
the original BERT model but
with different random seeds, which causes variations in the initial weights and order of
tr... | [
"# MultiBERTs - Seed 17\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT. We provide 25 BERT-base models trained with\nsimilar hyper-parameters as\nthe original BERT model but\nwith different random seeds, which causes variations in the initial weights and o... | [
"TAGS\n#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_17 #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# MultiBERTs - Seed 17\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT.... |
null | transformers |
# MultiBERTs - Seed 18
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://github.com/google-research/bert) but
with different random seeds, which causes variat... | {"language": "en", "license": "apache-2.0", "tags": ["multiberts", "multiberts-seed_18"]} | google/multiberts-seed_18 | null | [
"transformers",
"pytorch",
"tf",
"bert",
"pretraining",
"multiberts",
"multiberts-seed_18",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2106.16163",
"1908.08962"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_18 #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us
|
# MultiBERTs - Seed 18
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
the original BERT model but
with different random seeds, which causes variations in the initial weights and order of
tr... | [
"# MultiBERTs - Seed 18\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT. We provide 25 BERT-base models trained with\nsimilar hyper-parameters as\nthe original BERT model but\nwith different random seeds, which causes variations in the initial weights and o... | [
"TAGS\n#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_18 #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# MultiBERTs - Seed 18\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT.... |
null | transformers |
# MultiBERTs - Seed 19
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://github.com/google-research/bert) but
with different random seeds, which causes variat... | {"language": "en", "license": "apache-2.0", "tags": ["multiberts", "multiberts-seed_19"]} | google/multiberts-seed_19 | null | [
"transformers",
"pytorch",
"tf",
"bert",
"pretraining",
"multiberts",
"multiberts-seed_19",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2106.16163",
"1908.08962"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_19 #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us
|
# MultiBERTs - Seed 19
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
the original BERT model but
with different random seeds, which causes variations in the initial weights and order of
tr... | [
"# MultiBERTs - Seed 19\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT. We provide 25 BERT-base models trained with\nsimilar hyper-parameters as\nthe original BERT model but\nwith different random seeds, which causes variations in the initial weights and o... | [
"TAGS\n#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_19 #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# MultiBERTs - Seed 19\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT.... |
null | transformers |
# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 0k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://github.com/google-research/bert) but
with different ... | {"language": "en", "license": "apache-2.0", "tags": ["multiberts", "multiberts-seed_2", "multiberts-seed_2-step_0k"]} | google/multiberts-seed_2-step_0k | null | [
"transformers",
"pytorch",
"tf",
"bert",
"pretraining",
"multiberts",
"multiberts-seed_2",
"multiberts-seed_2-step_0k",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2106.16163",
"1908.08962"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_2 #multiberts-seed_2-step_0k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us
|
# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 0k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
the original BERT model but
with different random seeds, which causes variations in th... | [
"# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 0k\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT. We provide 25 BERT-base models trained with\nsimilar hyper-parameters as\nthe original BERT model but\nwith different random seeds, which causes variat... | [
"TAGS\n#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_2 #multiberts-seed_2-step_0k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 0k\n\nMultiBERTs is a collection of checkpoints and... |
null | transformers |
# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 1000k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://github.com/google-research/bert) but
with differe... | {"language": "en", "license": "apache-2.0", "tags": ["multiberts", "multiberts-seed_2", "multiberts-seed_2-step_1000k"]} | google/multiberts-seed_2-step_1000k | null | [
"transformers",
"pytorch",
"tf",
"bert",
"pretraining",
"multiberts",
"multiberts-seed_2",
"multiberts-seed_2-step_1000k",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2106.16163",
"1908.08962"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_2 #multiberts-seed_2-step_1000k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us
|
# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 1000k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
the original BERT model but
with different random seeds, which causes variations in... | [
"# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 1000k\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT. We provide 25 BERT-base models trained with\nsimilar hyper-parameters as\nthe original BERT model but\nwith different random seeds, which causes var... | [
"TAGS\n#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_2 #multiberts-seed_2-step_1000k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 1000k\n\nMultiBERTs is a collection of checkpoin... |
null | transformers |
# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 100k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://github.com/google-research/bert) but
with differen... | {"language": "en", "license": "apache-2.0", "tags": ["multiberts", "multiberts-seed_2", "multiberts-seed_2-step_100k"]} | google/multiberts-seed_2-step_100k | null | [
"transformers",
"pytorch",
"tf",
"bert",
"pretraining",
"multiberts",
"multiberts-seed_2",
"multiberts-seed_2-step_100k",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2106.16163",
"1908.08962"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_2 #multiberts-seed_2-step_100k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us
|
# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 100k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
the original BERT model but
with different random seeds, which causes variations in ... | [
"# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 100k\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT. We provide 25 BERT-base models trained with\nsimilar hyper-parameters as\nthe original BERT model but\nwith different random seeds, which causes vari... | [
"TAGS\n#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_2 #multiberts-seed_2-step_100k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 100k\n\nMultiBERTs is a collection of checkpoints... |
null | transformers |
# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 1100k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://github.com/google-research/bert) but
with differe... | {"language": "en", "license": "apache-2.0", "tags": ["multiberts", "multiberts-seed_2", "multiberts-seed_2-step_1100k"]} | google/multiberts-seed_2-step_1100k | null | [
"transformers",
"pytorch",
"tf",
"bert",
"pretraining",
"multiberts",
"multiberts-seed_2",
"multiberts-seed_2-step_1100k",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2106.16163",
"1908.08962"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_2 #multiberts-seed_2-step_1100k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us
|
# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 1100k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
the original BERT model but
with different random seeds, which causes variations in... | [
"# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 1100k\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT. We provide 25 BERT-base models trained with\nsimilar hyper-parameters as\nthe original BERT model but\nwith different random seeds, which causes var... | [
"TAGS\n#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_2 #multiberts-seed_2-step_1100k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 1100k\n\nMultiBERTs is a collection of checkpoin... |
null | transformers |
# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 1200k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://github.com/google-research/bert) but
with differe... | {"language": "en", "license": "apache-2.0", "tags": ["multiberts", "multiberts-seed_2", "multiberts-seed_2-step_1200k"]} | google/multiberts-seed_2-step_1200k | null | [
"transformers",
"pytorch",
"tf",
"bert",
"pretraining",
"multiberts",
"multiberts-seed_2",
"multiberts-seed_2-step_1200k",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2106.16163",
"1908.08962"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_2 #multiberts-seed_2-step_1200k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us
|
# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 1200k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
the original BERT model but
with different random seeds, which causes variations in... | [
"# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 1200k\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT. We provide 25 BERT-base models trained with\nsimilar hyper-parameters as\nthe original BERT model but\nwith different random seeds, which causes var... | [
"TAGS\n#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_2 #multiberts-seed_2-step_1200k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 1200k\n\nMultiBERTs is a collection of checkpoin... |
null | transformers |
# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 120k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://github.com/google-research/bert) but
with differen... | {"language": "en", "license": "apache-2.0", "tags": ["multiberts", "multiberts-seed_2", "multiberts-seed_2-step_120k"]} | google/multiberts-seed_2-step_120k | null | [
"transformers",
"pytorch",
"tf",
"bert",
"pretraining",
"multiberts",
"multiberts-seed_2",
"multiberts-seed_2-step_120k",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2106.16163",
"1908.08962"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_2 #multiberts-seed_2-step_120k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us
|
# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 120k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
the original BERT model but
with different random seeds, which causes variations in ... | [
"# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 120k\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT. We provide 25 BERT-base models trained with\nsimilar hyper-parameters as\nthe original BERT model but\nwith different random seeds, which causes vari... | [
"TAGS\n#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_2 #multiberts-seed_2-step_120k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 120k\n\nMultiBERTs is a collection of checkpoints... |
null | transformers |
# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 1300k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://github.com/google-research/bert) but
with differe... | {"language": "en", "license": "apache-2.0", "tags": ["multiberts", "multiberts-seed_2", "multiberts-seed_2-step_1300k"]} | google/multiberts-seed_2-step_1300k | null | [
"transformers",
"pytorch",
"tf",
"bert",
"pretraining",
"multiberts",
"multiberts-seed_2",
"multiberts-seed_2-step_1300k",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2106.16163",
"1908.08962"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_2 #multiberts-seed_2-step_1300k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us
|
# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 1300k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
the original BERT model but
with different random seeds, which causes variations in... | [
"# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 1300k\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT. We provide 25 BERT-base models trained with\nsimilar hyper-parameters as\nthe original BERT model but\nwith different random seeds, which causes var... | [
"TAGS\n#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_2 #multiberts-seed_2-step_1300k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 1300k\n\nMultiBERTs is a collection of checkpoin... |
null | transformers |
# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 1400k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://github.com/google-research/bert) but
with differe... | {"language": "en", "license": "apache-2.0", "tags": ["multiberts", "multiberts-seed_2", "multiberts-seed_2-step_1400k"]} | google/multiberts-seed_2-step_1400k | null | [
"transformers",
"pytorch",
"tf",
"bert",
"pretraining",
"multiberts",
"multiberts-seed_2",
"multiberts-seed_2-step_1400k",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2106.16163",
"1908.08962"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_2 #multiberts-seed_2-step_1400k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us
|
# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 1400k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
the original BERT model but
with different random seeds, which causes variations in... | [
"# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 1400k\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT. We provide 25 BERT-base models trained with\nsimilar hyper-parameters as\nthe original BERT model but\nwith different random seeds, which causes var... | [
"TAGS\n#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_2 #multiberts-seed_2-step_1400k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 1400k\n\nMultiBERTs is a collection of checkpoin... |
null | transformers |
# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 140k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://github.com/google-research/bert) but
with differen... | {"language": "en", "license": "apache-2.0", "tags": ["multiberts", "multiberts-seed_2", "multiberts-seed_2-step_140k"]} | google/multiberts-seed_2-step_140k | null | [
"transformers",
"pytorch",
"tf",
"bert",
"pretraining",
"multiberts",
"multiberts-seed_2",
"multiberts-seed_2-step_140k",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2106.16163",
"1908.08962"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_2 #multiberts-seed_2-step_140k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us
|
# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 140k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
the original BERT model but
with different random seeds, which causes variations in ... | [
"# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 140k\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT. We provide 25 BERT-base models trained with\nsimilar hyper-parameters as\nthe original BERT model but\nwith different random seeds, which causes vari... | [
"TAGS\n#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_2 #multiberts-seed_2-step_140k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 140k\n\nMultiBERTs is a collection of checkpoints... |
null | transformers |
# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 1500k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://github.com/google-research/bert) but
with differe... | {"language": "en", "license": "apache-2.0", "tags": ["multiberts", "multiberts-seed_2", "multiberts-seed_2-step_1500k"]} | google/multiberts-seed_2-step_1500k | null | [
"transformers",
"pytorch",
"tf",
"bert",
"pretraining",
"multiberts",
"multiberts-seed_2",
"multiberts-seed_2-step_1500k",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2106.16163",
"1908.08962"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_2 #multiberts-seed_2-step_1500k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us
|
# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 1500k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
the original BERT model but
with different random seeds, which causes variations in... | [
"# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 1500k\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT. We provide 25 BERT-base models trained with\nsimilar hyper-parameters as\nthe original BERT model but\nwith different random seeds, which causes var... | [
"TAGS\n#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_2 #multiberts-seed_2-step_1500k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 1500k\n\nMultiBERTs is a collection of checkpoin... |
null | transformers |
# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 1600k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://github.com/google-research/bert) but
with differe... | {"language": "en", "license": "apache-2.0", "tags": ["multiberts", "multiberts-seed_2", "multiberts-seed_2-step_1600k"]} | google/multiberts-seed_2-step_1600k | null | [
"transformers",
"pytorch",
"tf",
"bert",
"pretraining",
"multiberts",
"multiberts-seed_2",
"multiberts-seed_2-step_1600k",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2106.16163",
"1908.08962"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_2 #multiberts-seed_2-step_1600k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us
|
# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 1600k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
the original BERT model but
with different random seeds, which causes variations in... | [
"# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 1600k\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT. We provide 25 BERT-base models trained with\nsimilar hyper-parameters as\nthe original BERT model but\nwith different random seeds, which causes var... | [
"TAGS\n#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_2 #multiberts-seed_2-step_1600k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 1600k\n\nMultiBERTs is a collection of checkpoin... |
null | transformers |
# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 160k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://github.com/google-research/bert) but
with differen... | {"language": "en", "license": "apache-2.0", "tags": ["multiberts", "multiberts-seed_2", "multiberts-seed_2-step_160k"]} | google/multiberts-seed_2-step_160k | null | [
"transformers",
"pytorch",
"tf",
"bert",
"pretraining",
"multiberts",
"multiberts-seed_2",
"multiberts-seed_2-step_160k",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2106.16163",
"1908.08962"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_2 #multiberts-seed_2-step_160k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us
|
# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 160k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
the original BERT model but
with different random seeds, which causes variations in ... | [
"# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 160k\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT. We provide 25 BERT-base models trained with\nsimilar hyper-parameters as\nthe original BERT model but\nwith different random seeds, which causes vari... | [
"TAGS\n#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_2 #multiberts-seed_2-step_160k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 160k\n\nMultiBERTs is a collection of checkpoints... |
null | transformers |
# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 1700k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://github.com/google-research/bert) but
with differe... | {"language": "en", "license": "apache-2.0", "tags": ["multiberts", "multiberts-seed_2", "multiberts-seed_2-step_1700k"]} | google/multiberts-seed_2-step_1700k | null | [
"transformers",
"pytorch",
"tf",
"bert",
"pretraining",
"multiberts",
"multiberts-seed_2",
"multiberts-seed_2-step_1700k",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2106.16163",
"1908.08962"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_2 #multiberts-seed_2-step_1700k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us
|
# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 1700k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
the original BERT model but
with different random seeds, which causes variations in... | [
"# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 1700k\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT. We provide 25 BERT-base models trained with\nsimilar hyper-parameters as\nthe original BERT model but\nwith different random seeds, which causes var... | [
"TAGS\n#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_2 #multiberts-seed_2-step_1700k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 1700k\n\nMultiBERTs is a collection of checkpoin... |
null | transformers |
# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 1800k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://github.com/google-research/bert) but
with differe... | {"language": "en", "license": "apache-2.0", "tags": ["multiberts", "multiberts-seed_2", "multiberts-seed_2-step_1800k"]} | google/multiberts-seed_2-step_1800k | null | [
"transformers",
"pytorch",
"tf",
"bert",
"pretraining",
"multiberts",
"multiberts-seed_2",
"multiberts-seed_2-step_1800k",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2106.16163",
"1908.08962"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_2 #multiberts-seed_2-step_1800k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us
|
# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 1800k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
the original BERT model but
with different random seeds, which causes variations in... | [
"# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 1800k\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT. We provide 25 BERT-base models trained with\nsimilar hyper-parameters as\nthe original BERT model but\nwith different random seeds, which causes var... | [
"TAGS\n#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_2 #multiberts-seed_2-step_1800k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 1800k\n\nMultiBERTs is a collection of checkpoin... |
null | transformers |
# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 180k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://github.com/google-research/bert) but
with differen... | {"language": "en", "license": "apache-2.0", "tags": ["multiberts", "multiberts-seed_2", "multiberts-seed_2-step_180k"]} | google/multiberts-seed_2-step_180k | null | [
"transformers",
"pytorch",
"tf",
"bert",
"pretraining",
"multiberts",
"multiberts-seed_2",
"multiberts-seed_2-step_180k",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2106.16163",
"1908.08962"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_2 #multiberts-seed_2-step_180k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us
|
# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 180k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
the original BERT model but
with different random seeds, which causes variations in ... | [
"# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 180k\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT. We provide 25 BERT-base models trained with\nsimilar hyper-parameters as\nthe original BERT model but\nwith different random seeds, which causes vari... | [
"TAGS\n#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_2 #multiberts-seed_2-step_180k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 180k\n\nMultiBERTs is a collection of checkpoints... |
null | transformers |
# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 1900k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://github.com/google-research/bert) but
with differe... | {"language": "en", "license": "apache-2.0", "tags": ["multiberts", "multiberts-seed_2", "multiberts-seed_2-step_1900k"]} | google/multiberts-seed_2-step_1900k | null | [
"transformers",
"pytorch",
"tf",
"bert",
"pretraining",
"multiberts",
"multiberts-seed_2",
"multiberts-seed_2-step_1900k",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2106.16163",
"1908.08962"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_2 #multiberts-seed_2-step_1900k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us
|
# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 1900k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
the original BERT model but
with different random seeds, which causes variations in... | [
"# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 1900k\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT. We provide 25 BERT-base models trained with\nsimilar hyper-parameters as\nthe original BERT model but\nwith different random seeds, which causes var... | [
"TAGS\n#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_2 #multiberts-seed_2-step_1900k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 1900k\n\nMultiBERTs is a collection of checkpoin... |
null | transformers |
# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 2000k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://github.com/google-research/bert) but
with differe... | {"language": "en", "license": "apache-2.0", "tags": ["multiberts", "multiberts-seed_2", "multiberts-seed_2-step_2000k"]} | google/multiberts-seed_2-step_2000k | null | [
"transformers",
"pytorch",
"tf",
"bert",
"pretraining",
"multiberts",
"multiberts-seed_2",
"multiberts-seed_2-step_2000k",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2106.16163",
"1908.08962"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_2 #multiberts-seed_2-step_2000k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us
|
# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 2000k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
the original BERT model but
with different random seeds, which causes variations in... | [
"# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 2000k\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT. We provide 25 BERT-base models trained with\nsimilar hyper-parameters as\nthe original BERT model but\nwith different random seeds, which causes var... | [
"TAGS\n#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_2 #multiberts-seed_2-step_2000k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 2000k\n\nMultiBERTs is a collection of checkpoin... |
null | transformers |
# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 200k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://github.com/google-research/bert) but
with differen... | {"language": "en", "license": "apache-2.0", "tags": ["multiberts", "multiberts-seed_2", "multiberts-seed_2-step_200k"]} | google/multiberts-seed_2-step_200k | null | [
"transformers",
"pytorch",
"tf",
"bert",
"pretraining",
"multiberts",
"multiberts-seed_2",
"multiberts-seed_2-step_200k",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2106.16163",
"1908.08962"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_2 #multiberts-seed_2-step_200k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us
|
# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 200k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
the original BERT model but
with different random seeds, which causes variations in ... | [
"# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 200k\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT. We provide 25 BERT-base models trained with\nsimilar hyper-parameters as\nthe original BERT model but\nwith different random seeds, which causes vari... | [
"TAGS\n#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_2 #multiberts-seed_2-step_200k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 200k\n\nMultiBERTs is a collection of checkpoints... |
null | transformers |
# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 20k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://github.com/google-research/bert) but
with different... | {"language": "en", "license": "apache-2.0", "tags": ["multiberts", "multiberts-seed_2", "multiberts-seed_2-step_20k"]} | google/multiberts-seed_2-step_20k | null | [
"transformers",
"pytorch",
"tf",
"bert",
"pretraining",
"multiberts",
"multiberts-seed_2",
"multiberts-seed_2-step_20k",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2106.16163",
"1908.08962"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_2 #multiberts-seed_2-step_20k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us
|
# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 20k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
the original BERT model but
with different random seeds, which causes variations in t... | [
"# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 20k\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT. We provide 25 BERT-base models trained with\nsimilar hyper-parameters as\nthe original BERT model but\nwith different random seeds, which causes varia... | [
"TAGS\n#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_2 #multiberts-seed_2-step_20k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 20k\n\nMultiBERTs is a collection of checkpoints a... |
null | transformers |
# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 300k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://github.com/google-research/bert) but
with differen... | {"language": "en", "license": "apache-2.0", "tags": ["multiberts", "multiberts-seed_2", "multiberts-seed_2-step_300k"]} | google/multiberts-seed_2-step_300k | null | [
"transformers",
"pytorch",
"tf",
"bert",
"pretraining",
"multiberts",
"multiberts-seed_2",
"multiberts-seed_2-step_300k",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2106.16163",
"1908.08962"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_2 #multiberts-seed_2-step_300k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us
|
# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 300k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
the original BERT model but
with different random seeds, which causes variations in ... | [
"# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 300k\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT. We provide 25 BERT-base models trained with\nsimilar hyper-parameters as\nthe original BERT model but\nwith different random seeds, which causes vari... | [
"TAGS\n#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_2 #multiberts-seed_2-step_300k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 300k\n\nMultiBERTs is a collection of checkpoints... |
null | transformers |
# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 400k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://github.com/google-research/bert) but
with differen... | {"language": "en", "license": "apache-2.0", "tags": ["multiberts", "multiberts-seed_2", "multiberts-seed_2-step_400k"]} | google/multiberts-seed_2-step_400k | null | [
"transformers",
"pytorch",
"tf",
"bert",
"pretraining",
"multiberts",
"multiberts-seed_2",
"multiberts-seed_2-step_400k",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2106.16163",
"1908.08962"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_2 #multiberts-seed_2-step_400k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us
|
# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 400k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
the original BERT model but
with different random seeds, which causes variations in ... | [
"# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 400k\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT. We provide 25 BERT-base models trained with\nsimilar hyper-parameters as\nthe original BERT model but\nwith different random seeds, which causes vari... | [
"TAGS\n#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_2 #multiberts-seed_2-step_400k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 400k\n\nMultiBERTs is a collection of checkpoints... |
null | transformers |
# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 40k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://github.com/google-research/bert) but
with different... | {"language": "en", "license": "apache-2.0", "tags": ["multiberts", "multiberts-seed_2", "multiberts-seed_2-step_40k"]} | google/multiberts-seed_2-step_40k | null | [
"transformers",
"pytorch",
"tf",
"bert",
"pretraining",
"multiberts",
"multiberts-seed_2",
"multiberts-seed_2-step_40k",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2106.16163",
"1908.08962"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_2 #multiberts-seed_2-step_40k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us
|
# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 40k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
the original BERT model but
with different random seeds, which causes variations in t... | [
"# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 40k\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT. We provide 25 BERT-base models trained with\nsimilar hyper-parameters as\nthe original BERT model but\nwith different random seeds, which causes varia... | [
"TAGS\n#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_2 #multiberts-seed_2-step_40k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 40k\n\nMultiBERTs is a collection of checkpoints a... |
null | transformers |
# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 500k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://github.com/google-research/bert) but
with differen... | {"language": "en", "license": "apache-2.0", "tags": ["multiberts", "multiberts-seed_2", "multiberts-seed_2-step_500k"]} | google/multiberts-seed_2-step_500k | null | [
"transformers",
"pytorch",
"tf",
"bert",
"pretraining",
"multiberts",
"multiberts-seed_2",
"multiberts-seed_2-step_500k",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2106.16163",
"1908.08962"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_2 #multiberts-seed_2-step_500k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us
|
# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 500k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
the original BERT model but
with different random seeds, which causes variations in ... | [
"# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 500k\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT. We provide 25 BERT-base models trained with\nsimilar hyper-parameters as\nthe original BERT model but\nwith different random seeds, which causes vari... | [
"TAGS\n#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_2 #multiberts-seed_2-step_500k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 500k\n\nMultiBERTs is a collection of checkpoints... |
null | transformers |
# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 600k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://github.com/google-research/bert) but
with differen... | {"language": "en", "license": "apache-2.0", "tags": ["multiberts", "multiberts-seed_2", "multiberts-seed_2-step_600k"]} | google/multiberts-seed_2-step_600k | null | [
"transformers",
"pytorch",
"tf",
"bert",
"pretraining",
"multiberts",
"multiberts-seed_2",
"multiberts-seed_2-step_600k",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2106.16163",
"1908.08962"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_2 #multiberts-seed_2-step_600k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us
|
# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 600k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
the original BERT model but
with different random seeds, which causes variations in ... | [
"# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 600k\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT. We provide 25 BERT-base models trained with\nsimilar hyper-parameters as\nthe original BERT model but\nwith different random seeds, which causes vari... | [
"TAGS\n#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_2 #multiberts-seed_2-step_600k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 600k\n\nMultiBERTs is a collection of checkpoints... |
null | transformers |
# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 60k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://github.com/google-research/bert) but
with different... | {"language": "en", "license": "apache-2.0", "tags": ["multiberts", "multiberts-seed_2", "multiberts-seed_2-step_60k"]} | google/multiberts-seed_2-step_60k | null | [
"transformers",
"pytorch",
"tf",
"bert",
"pretraining",
"multiberts",
"multiberts-seed_2",
"multiberts-seed_2-step_60k",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2106.16163",
"1908.08962"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_2 #multiberts-seed_2-step_60k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us
|
# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 60k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
the original BERT model but
with different random seeds, which causes variations in t... | [
"# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 60k\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT. We provide 25 BERT-base models trained with\nsimilar hyper-parameters as\nthe original BERT model but\nwith different random seeds, which causes varia... | [
"TAGS\n#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_2 #multiberts-seed_2-step_60k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 60k\n\nMultiBERTs is a collection of checkpoints a... |
null | transformers |
# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 700k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://github.com/google-research/bert) but
with differen... | {"language": "en", "license": "apache-2.0", "tags": ["multiberts", "multiberts-seed_2", "multiberts-seed_2-step_700k"]} | google/multiberts-seed_2-step_700k | null | [
"transformers",
"pytorch",
"tf",
"bert",
"pretraining",
"multiberts",
"multiberts-seed_2",
"multiberts-seed_2-step_700k",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2106.16163",
"1908.08962"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_2 #multiberts-seed_2-step_700k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us
|
# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 700k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
the original BERT model but
with different random seeds, which causes variations in ... | [
"# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 700k\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT. We provide 25 BERT-base models trained with\nsimilar hyper-parameters as\nthe original BERT model but\nwith different random seeds, which causes vari... | [
"TAGS\n#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_2 #multiberts-seed_2-step_700k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 700k\n\nMultiBERTs is a collection of checkpoints... |
null | transformers |
# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 800k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://github.com/google-research/bert) but
with differen... | {"language": "en", "license": "apache-2.0", "tags": ["multiberts", "multiberts-seed_2", "multiberts-seed_2-step_800k"]} | google/multiberts-seed_2-step_800k | null | [
"transformers",
"pytorch",
"tf",
"bert",
"pretraining",
"multiberts",
"multiberts-seed_2",
"multiberts-seed_2-step_800k",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2106.16163",
"1908.08962"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_2 #multiberts-seed_2-step_800k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us
|
# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 800k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
the original BERT model but
with different random seeds, which causes variations in ... | [
"# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 800k\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT. We provide 25 BERT-base models trained with\nsimilar hyper-parameters as\nthe original BERT model but\nwith different random seeds, which causes vari... | [
"TAGS\n#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_2 #multiberts-seed_2-step_800k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 800k\n\nMultiBERTs is a collection of checkpoints... |
null | transformers |
# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 80k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://github.com/google-research/bert) but
with different... | {"language": "en", "license": "apache-2.0", "tags": ["multiberts", "multiberts-seed_2", "multiberts-seed_2-step_80k"]} | google/multiberts-seed_2-step_80k | null | [
"transformers",
"pytorch",
"tf",
"bert",
"pretraining",
"multiberts",
"multiberts-seed_2",
"multiberts-seed_2-step_80k",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2106.16163",
"1908.08962"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_2 #multiberts-seed_2-step_80k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us
|
# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 80k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
the original BERT model but
with different random seeds, which causes variations in t... | [
"# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 80k\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT. We provide 25 BERT-base models trained with\nsimilar hyper-parameters as\nthe original BERT model but\nwith different random seeds, which causes varia... | [
"TAGS\n#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_2 #multiberts-seed_2-step_80k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 80k\n\nMultiBERTs is a collection of checkpoints a... |
null | transformers |
# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 900k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://github.com/google-research/bert) but
with differen... | {"language": "en", "license": "apache-2.0", "tags": ["multiberts", "multiberts-seed_2", "multiberts-seed_2-step_900k"]} | google/multiberts-seed_2-step_900k | null | [
"transformers",
"pytorch",
"tf",
"bert",
"pretraining",
"multiberts",
"multiberts-seed_2",
"multiberts-seed_2-step_900k",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2106.16163",
"1908.08962"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_2 #multiberts-seed_2-step_900k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us
|
# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 900k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
the original BERT model but
with different random seeds, which causes variations in ... | [
"# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 900k\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT. We provide 25 BERT-base models trained with\nsimilar hyper-parameters as\nthe original BERT model but\nwith different random seeds, which causes vari... | [
"TAGS\n#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_2 #multiberts-seed_2-step_900k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 900k\n\nMultiBERTs is a collection of checkpoints... |
null | transformers |
# MultiBERTs - Seed 2
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://github.com/google-research/bert) but
with different random seeds, which causes variati... | {"language": "en", "license": "apache-2.0", "tags": ["multiberts", "multiberts-seed_2"]} | google/multiberts-seed_2 | null | [
"transformers",
"pytorch",
"tf",
"bert",
"pretraining",
"multiberts",
"multiberts-seed_2",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2106.16163",
"1908.08962"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_2 #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us
|
# MultiBERTs - Seed 2
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
the original BERT model but
with different random seeds, which causes variations in the initial weights and order of
tra... | [
"# MultiBERTs - Seed 2\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT. We provide 25 BERT-base models trained with\nsimilar hyper-parameters as\nthe original BERT model but\nwith different random seeds, which causes variations in the initial weights and or... | [
"TAGS\n#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_2 #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# MultiBERTs - Seed 2\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT. W... |
null | transformers |
# MultiBERTs - Seed 20
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://github.com/google-research/bert) but
with different random seeds, which causes variat... | {"language": "en", "license": "apache-2.0", "tags": ["multiberts", "multiberts-seed_20"]} | google/multiberts-seed_20 | null | [
"transformers",
"pytorch",
"tf",
"bert",
"pretraining",
"multiberts",
"multiberts-seed_20",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2106.16163",
"1908.08962"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_20 #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us
|
# MultiBERTs - Seed 20
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
the original BERT model but
with different random seeds, which causes variations in the initial weights and order of
tr... | [
"# MultiBERTs - Seed 20\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT. We provide 25 BERT-base models trained with\nsimilar hyper-parameters as\nthe original BERT model but\nwith different random seeds, which causes variations in the initial weights and o... | [
"TAGS\n#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_20 #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# MultiBERTs - Seed 20\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT.... |
null | transformers |
# MultiBERTs - Seed 21
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://github.com/google-research/bert) but
with different random seeds, which causes variat... | {"language": "en", "license": "apache-2.0", "tags": ["multiberts", "multiberts-seed_21"]} | google/multiberts-seed_21 | null | [
"transformers",
"pytorch",
"tf",
"bert",
"pretraining",
"multiberts",
"multiberts-seed_21",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2106.16163",
"1908.08962"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_21 #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us
|
# MultiBERTs - Seed 21
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
the original BERT model but
with different random seeds, which causes variations in the initial weights and order of
tr... | [
"# MultiBERTs - Seed 21\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT. We provide 25 BERT-base models trained with\nsimilar hyper-parameters as\nthe original BERT model but\nwith different random seeds, which causes variations in the initial weights and o... | [
"TAGS\n#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_21 #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# MultiBERTs - Seed 21\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT.... |
null | transformers |
# MultiBERTs - Seed 22
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://github.com/google-research/bert) but
with different random seeds, which causes variat... | {"language": "en", "license": "apache-2.0", "tags": ["multiberts", "multiberts-seed_22"]} | google/multiberts-seed_22 | null | [
"transformers",
"pytorch",
"tf",
"bert",
"pretraining",
"multiberts",
"multiberts-seed_22",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2106.16163",
"1908.08962"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_22 #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us
|
# MultiBERTs - Seed 22
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
the original BERT model but
with different random seeds, which causes variations in the initial weights and order of
tr... | [
"# MultiBERTs - Seed 22\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT. We provide 25 BERT-base models trained with\nsimilar hyper-parameters as\nthe original BERT model but\nwith different random seeds, which causes variations in the initial weights and o... | [
"TAGS\n#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_22 #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# MultiBERTs - Seed 22\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT.... |
null | transformers |
# MultiBERTs - Seed 23
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://github.com/google-research/bert) but
with different random seeds, which causes variat... | {"language": "en", "license": "apache-2.0", "tags": ["multiberts", "multiberts-seed_23"]} | google/multiberts-seed_23 | null | [
"transformers",
"pytorch",
"tf",
"bert",
"pretraining",
"multiberts",
"multiberts-seed_23",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2106.16163",
"1908.08962"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_23 #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us
|
# MultiBERTs - Seed 23
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
the original BERT model but
with different random seeds, which causes variations in the initial weights and order of
tr... | [
"# MultiBERTs - Seed 23\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT. We provide 25 BERT-base models trained with\nsimilar hyper-parameters as\nthe original BERT model but\nwith different random seeds, which causes variations in the initial weights and o... | [
"TAGS\n#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_23 #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# MultiBERTs - Seed 23\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT.... |
null | transformers |
# MultiBERTs - Seed 24
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://github.com/google-research/bert) but
with different random seeds, which causes variat... | {"language": "en", "license": "apache-2.0", "tags": ["multiberts", "multiberts-seed_24"]} | google/multiberts-seed_24 | null | [
"transformers",
"pytorch",
"tf",
"bert",
"pretraining",
"multiberts",
"multiberts-seed_24",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2106.16163",
"1908.08962"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_24 #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us
|
# MultiBERTs - Seed 24
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
the original BERT model but
with different random seeds, which causes variations in the initial weights and order of
tr... | [
"# MultiBERTs - Seed 24\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT. We provide 25 BERT-base models trained with\nsimilar hyper-parameters as\nthe original BERT model but\nwith different random seeds, which causes variations in the initial weights and o... | [
"TAGS\n#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_24 #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# MultiBERTs - Seed 24\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT.... |
null | transformers |
# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 0k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://github.com/google-research/bert) but
with different ... | {"language": "en", "license": "apache-2.0", "tags": ["multiberts", "multiberts-seed_3", "multiberts-seed_3-step_0k"]} | google/multiberts-seed_3-step_0k | null | [
"transformers",
"pytorch",
"tf",
"bert",
"pretraining",
"multiberts",
"multiberts-seed_3",
"multiberts-seed_3-step_0k",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2106.16163",
"1908.08962"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_3 #multiberts-seed_3-step_0k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us
|
# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 0k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
the original BERT model but
with different random seeds, which causes variations in th... | [
"# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 0k\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT. We provide 25 BERT-base models trained with\nsimilar hyper-parameters as\nthe original BERT model but\nwith different random seeds, which causes variat... | [
"TAGS\n#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_3 #multiberts-seed_3-step_0k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 0k\n\nMultiBERTs is a collection of checkpoints and... |
null | transformers |
# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 1000k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://github.com/google-research/bert) but
with differe... | {"language": "en", "license": "apache-2.0", "tags": ["multiberts", "multiberts-seed_3", "multiberts-seed_3-step_1000k"]} | google/multiberts-seed_3-step_1000k | null | [
"transformers",
"pytorch",
"tf",
"bert",
"pretraining",
"multiberts",
"multiberts-seed_3",
"multiberts-seed_3-step_1000k",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2106.16163",
"1908.08962"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_3 #multiberts-seed_3-step_1000k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us
|
# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 1000k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
the original BERT model but
with different random seeds, which causes variations in... | [
"# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 1000k\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT. We provide 25 BERT-base models trained with\nsimilar hyper-parameters as\nthe original BERT model but\nwith different random seeds, which causes var... | [
"TAGS\n#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_3 #multiberts-seed_3-step_1000k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 1000k\n\nMultiBERTs is a collection of checkpoin... |
null | transformers |
# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 100k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://github.com/google-research/bert) but
with differen... | {"language": "en", "license": "apache-2.0", "tags": ["multiberts", "multiberts-seed_3", "multiberts-seed_3-step_100k"]} | google/multiberts-seed_3-step_100k | null | [
"transformers",
"pytorch",
"tf",
"bert",
"pretraining",
"multiberts",
"multiberts-seed_3",
"multiberts-seed_3-step_100k",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2106.16163",
"1908.08962"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_3 #multiberts-seed_3-step_100k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us
|
# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 100k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
the original BERT model but
with different random seeds, which causes variations in ... | [
"# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 100k\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT. We provide 25 BERT-base models trained with\nsimilar hyper-parameters as\nthe original BERT model but\nwith different random seeds, which causes vari... | [
"TAGS\n#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_3 #multiberts-seed_3-step_100k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 100k\n\nMultiBERTs is a collection of checkpoints... |
null | transformers |
# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 1100k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://github.com/google-research/bert) but
with differe... | {"language": "en", "license": "apache-2.0", "tags": ["multiberts", "multiberts-seed_3", "multiberts-seed_3-step_1100k"]} | google/multiberts-seed_3-step_1100k | null | [
"transformers",
"pytorch",
"tf",
"bert",
"pretraining",
"multiberts",
"multiberts-seed_3",
"multiberts-seed_3-step_1100k",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2106.16163",
"1908.08962"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_3 #multiberts-seed_3-step_1100k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us
|
# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 1100k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
the original BERT model but
with different random seeds, which causes variations in... | [
"# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 1100k\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT. We provide 25 BERT-base models trained with\nsimilar hyper-parameters as\nthe original BERT model but\nwith different random seeds, which causes var... | [
"TAGS\n#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_3 #multiberts-seed_3-step_1100k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 1100k\n\nMultiBERTs is a collection of checkpoin... |
null | transformers |
# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 1200k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://github.com/google-research/bert) but
with differe... | {"language": "en", "license": "apache-2.0", "tags": ["multiberts", "multiberts-seed_3", "multiberts-seed_3-step_1200k"]} | google/multiberts-seed_3-step_1200k | null | [
"transformers",
"pytorch",
"tf",
"bert",
"pretraining",
"multiberts",
"multiberts-seed_3",
"multiberts-seed_3-step_1200k",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2106.16163",
"1908.08962"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_3 #multiberts-seed_3-step_1200k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us
|
# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 1200k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
the original BERT model but
with different random seeds, which causes variations in... | [
"# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 1200k\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT. We provide 25 BERT-base models trained with\nsimilar hyper-parameters as\nthe original BERT model but\nwith different random seeds, which causes var... | [
"TAGS\n#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_3 #multiberts-seed_3-step_1200k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 1200k\n\nMultiBERTs is a collection of checkpoin... |
null | transformers |
# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 120k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://github.com/google-research/bert) but
with differen... | {"language": "en", "license": "apache-2.0", "tags": ["multiberts", "multiberts-seed_3", "multiberts-seed_3-step_120k"]} | google/multiberts-seed_3-step_120k | null | [
"transformers",
"pytorch",
"tf",
"bert",
"pretraining",
"multiberts",
"multiberts-seed_3",
"multiberts-seed_3-step_120k",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2106.16163",
"1908.08962"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_3 #multiberts-seed_3-step_120k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us
|
# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 120k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
the original BERT model but
with different random seeds, which causes variations in ... | [
"# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 120k\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT. We provide 25 BERT-base models trained with\nsimilar hyper-parameters as\nthe original BERT model but\nwith different random seeds, which causes vari... | [
"TAGS\n#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_3 #multiberts-seed_3-step_120k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 120k\n\nMultiBERTs is a collection of checkpoints... |
null | transformers |
# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 1300k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://github.com/google-research/bert) but
with differe... | {"language": "en", "license": "apache-2.0", "tags": ["multiberts", "multiberts-seed_3", "multiberts-seed_3-step_1300k"]} | google/multiberts-seed_3-step_1300k | null | [
"transformers",
"pytorch",
"tf",
"bert",
"pretraining",
"multiberts",
"multiberts-seed_3",
"multiberts-seed_3-step_1300k",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2106.16163",
"1908.08962"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_3 #multiberts-seed_3-step_1300k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us
|
# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 1300k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
the original BERT model but
with different random seeds, which causes variations in... | [
"# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 1300k\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT. We provide 25 BERT-base models trained with\nsimilar hyper-parameters as\nthe original BERT model but\nwith different random seeds, which causes var... | [
"TAGS\n#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_3 #multiberts-seed_3-step_1300k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 1300k\n\nMultiBERTs is a collection of checkpoin... |
null | transformers |
# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 1400k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://github.com/google-research/bert) but
with differe... | {"language": "en", "license": "apache-2.0", "tags": ["multiberts", "multiberts-seed_3", "multiberts-seed_3-step_1400k"]} | google/multiberts-seed_3-step_1400k | null | [
"transformers",
"pytorch",
"tf",
"bert",
"pretraining",
"multiberts",
"multiberts-seed_3",
"multiberts-seed_3-step_1400k",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2106.16163",
"1908.08962"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_3 #multiberts-seed_3-step_1400k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us
|
# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 1400k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
the original BERT model but
with different random seeds, which causes variations in... | [
"# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 1400k\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT. We provide 25 BERT-base models trained with\nsimilar hyper-parameters as\nthe original BERT model but\nwith different random seeds, which causes var... | [
"TAGS\n#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_3 #multiberts-seed_3-step_1400k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 1400k\n\nMultiBERTs is a collection of checkpoin... |
null | transformers |
# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 140k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://github.com/google-research/bert) but
with differen... | {"language": "en", "license": "apache-2.0", "tags": ["multiberts", "multiberts-seed_3", "multiberts-seed_3-step_140k"]} | google/multiberts-seed_3-step_140k | null | [
"transformers",
"pytorch",
"tf",
"bert",
"pretraining",
"multiberts",
"multiberts-seed_3",
"multiberts-seed_3-step_140k",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2106.16163",
"1908.08962"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_3 #multiberts-seed_3-step_140k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us
|
# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 140k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
the original BERT model but
with different random seeds, which causes variations in ... | [
"# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 140k\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT. We provide 25 BERT-base models trained with\nsimilar hyper-parameters as\nthe original BERT model but\nwith different random seeds, which causes vari... | [
"TAGS\n#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_3 #multiberts-seed_3-step_140k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 140k\n\nMultiBERTs is a collection of checkpoints... |
null | transformers |
# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 1500k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://github.com/google-research/bert) but
with differe... | {"language": "en", "license": "apache-2.0", "tags": ["multiberts", "multiberts-seed_3", "multiberts-seed_3-step_1500k"]} | google/multiberts-seed_3-step_1500k | null | [
"transformers",
"pytorch",
"tf",
"bert",
"pretraining",
"multiberts",
"multiberts-seed_3",
"multiberts-seed_3-step_1500k",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2106.16163",
"1908.08962"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_3 #multiberts-seed_3-step_1500k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us
|
# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 1500k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
the original BERT model but
with different random seeds, which causes variations in... | [
"# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 1500k\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT. We provide 25 BERT-base models trained with\nsimilar hyper-parameters as\nthe original BERT model but\nwith different random seeds, which causes var... | [
"TAGS\n#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_3 #multiberts-seed_3-step_1500k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 1500k\n\nMultiBERTs is a collection of checkpoin... |
null | transformers |
# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 1600k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://github.com/google-research/bert) but
with differe... | {"language": "en", "license": "apache-2.0", "tags": ["multiberts", "multiberts-seed_3", "multiberts-seed_3-step_1600k"]} | google/multiberts-seed_3-step_1600k | null | [
"transformers",
"pytorch",
"tf",
"bert",
"pretraining",
"multiberts",
"multiberts-seed_3",
"multiberts-seed_3-step_1600k",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2106.16163",
"1908.08962"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_3 #multiberts-seed_3-step_1600k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us
|
# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 1600k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
the original BERT model but
with different random seeds, which causes variations in... | [
"# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 1600k\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT. We provide 25 BERT-base models trained with\nsimilar hyper-parameters as\nthe original BERT model but\nwith different random seeds, which causes var... | [
"TAGS\n#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_3 #multiberts-seed_3-step_1600k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 1600k\n\nMultiBERTs is a collection of checkpoin... |
null | transformers |
# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 160k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://github.com/google-research/bert) but
with differen... | {"language": "en", "license": "apache-2.0", "tags": ["multiberts", "multiberts-seed_3", "multiberts-seed_3-step_160k"]} | google/multiberts-seed_3-step_160k | null | [
"transformers",
"pytorch",
"tf",
"bert",
"pretraining",
"multiberts",
"multiberts-seed_3",
"multiberts-seed_3-step_160k",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2106.16163",
"1908.08962"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_3 #multiberts-seed_3-step_160k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us
|
# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 160k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
the original BERT model but
with different random seeds, which causes variations in ... | [
"# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 160k\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT. We provide 25 BERT-base models trained with\nsimilar hyper-parameters as\nthe original BERT model but\nwith different random seeds, which causes vari... | [
"TAGS\n#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_3 #multiberts-seed_3-step_160k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 160k\n\nMultiBERTs is a collection of checkpoints... |
null | transformers |
# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 1700k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://github.com/google-research/bert) but
with differe... | {"language": "en", "license": "apache-2.0", "tags": ["multiberts", "multiberts-seed_3", "multiberts-seed_3-step_1700k"]} | google/multiberts-seed_3-step_1700k | null | [
"transformers",
"pytorch",
"tf",
"bert",
"pretraining",
"multiberts",
"multiberts-seed_3",
"multiberts-seed_3-step_1700k",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2106.16163",
"1908.08962"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_3 #multiberts-seed_3-step_1700k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us
|
# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 1700k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
the original BERT model but
with different random seeds, which causes variations in... | [
"# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 1700k\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT. We provide 25 BERT-base models trained with\nsimilar hyper-parameters as\nthe original BERT model but\nwith different random seeds, which causes var... | [
"TAGS\n#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_3 #multiberts-seed_3-step_1700k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 1700k\n\nMultiBERTs is a collection of checkpoin... |
null | transformers |
# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 1800k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://github.com/google-research/bert) but
with differe... | {"language": "en", "license": "apache-2.0", "tags": ["multiberts", "multiberts-seed_3", "multiberts-seed_3-step_1800k"]} | google/multiberts-seed_3-step_1800k | null | [
"transformers",
"pytorch",
"tf",
"bert",
"pretraining",
"multiberts",
"multiberts-seed_3",
"multiberts-seed_3-step_1800k",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2106.16163",
"1908.08962"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_3 #multiberts-seed_3-step_1800k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us
|
# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 1800k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
the original BERT model but
with different random seeds, which causes variations in... | [
"# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 1800k\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT. We provide 25 BERT-base models trained with\nsimilar hyper-parameters as\nthe original BERT model but\nwith different random seeds, which causes var... | [
"TAGS\n#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_3 #multiberts-seed_3-step_1800k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 1800k\n\nMultiBERTs is a collection of checkpoin... |
null | transformers |
# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 180k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://github.com/google-research/bert) but
with differen... | {"language": "en", "license": "apache-2.0", "tags": ["multiberts", "multiberts-seed_3", "multiberts-seed_3-step_180k"]} | google/multiberts-seed_3-step_180k | null | [
"transformers",
"pytorch",
"tf",
"bert",
"pretraining",
"multiberts",
"multiberts-seed_3",
"multiberts-seed_3-step_180k",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2106.16163",
"1908.08962"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_3 #multiberts-seed_3-step_180k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us
|
# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 180k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
the original BERT model but
with different random seeds, which causes variations in ... | [
"# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 180k\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT. We provide 25 BERT-base models trained with\nsimilar hyper-parameters as\nthe original BERT model but\nwith different random seeds, which causes vari... | [
"TAGS\n#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_3 #multiberts-seed_3-step_180k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 180k\n\nMultiBERTs is a collection of checkpoints... |
null | transformers |
# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 1900k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://github.com/google-research/bert) but
with differe... | {"language": "en", "license": "apache-2.0", "tags": ["multiberts", "multiberts-seed_3", "multiberts-seed_3-step_1900k"]} | google/multiberts-seed_3-step_1900k | null | [
"transformers",
"pytorch",
"tf",
"bert",
"pretraining",
"multiberts",
"multiberts-seed_3",
"multiberts-seed_3-step_1900k",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2106.16163",
"1908.08962"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_3 #multiberts-seed_3-step_1900k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us
|
# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 1900k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
the original BERT model but
with different random seeds, which causes variations in... | [
"# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 1900k\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT. We provide 25 BERT-base models trained with\nsimilar hyper-parameters as\nthe original BERT model but\nwith different random seeds, which causes var... | [
"TAGS\n#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_3 #multiberts-seed_3-step_1900k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 1900k\n\nMultiBERTs is a collection of checkpoin... |
null | transformers |
# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 2000k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://github.com/google-research/bert) but
with differe... | {"language": "en", "license": "apache-2.0", "tags": ["multiberts", "multiberts-seed_3", "multiberts-seed_3-step_2000k"]} | google/multiberts-seed_3-step_2000k | null | [
"transformers",
"pytorch",
"tf",
"bert",
"pretraining",
"multiberts",
"multiberts-seed_3",
"multiberts-seed_3-step_2000k",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2106.16163",
"1908.08962"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_3 #multiberts-seed_3-step_2000k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us
|
# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 2000k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
the original BERT model but
with different random seeds, which causes variations in... | [
"# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 2000k\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT. We provide 25 BERT-base models trained with\nsimilar hyper-parameters as\nthe original BERT model but\nwith different random seeds, which causes var... | [
"TAGS\n#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_3 #multiberts-seed_3-step_2000k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 2000k\n\nMultiBERTs is a collection of checkpoin... |
null | transformers |
# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 200k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://github.com/google-research/bert) but
with differen... | {"language": "en", "license": "apache-2.0", "tags": ["multiberts", "multiberts-seed_3", "multiberts-seed_3-step_200k"]} | google/multiberts-seed_3-step_200k | null | [
"transformers",
"pytorch",
"tf",
"bert",
"pretraining",
"multiberts",
"multiberts-seed_3",
"multiberts-seed_3-step_200k",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2106.16163",
"1908.08962"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_3 #multiberts-seed_3-step_200k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us
|
# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 200k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
the original BERT model but
with different random seeds, which causes variations in ... | [
"# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 200k\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT. We provide 25 BERT-base models trained with\nsimilar hyper-parameters as\nthe original BERT model but\nwith different random seeds, which causes vari... | [
"TAGS\n#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_3 #multiberts-seed_3-step_200k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 200k\n\nMultiBERTs is a collection of checkpoints... |
null | transformers |
# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 20k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://github.com/google-research/bert) but
with different... | {"language": "en", "license": "apache-2.0", "tags": ["multiberts", "multiberts-seed_3", "multiberts-seed_3-step_20k"]} | google/multiberts-seed_3-step_20k | null | [
"transformers",
"pytorch",
"tf",
"bert",
"pretraining",
"multiberts",
"multiberts-seed_3",
"multiberts-seed_3-step_20k",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2106.16163",
"1908.08962"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_3 #multiberts-seed_3-step_20k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us
|
# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 20k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
the original BERT model but
with different random seeds, which causes variations in t... | [
"# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 20k\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT. We provide 25 BERT-base models trained with\nsimilar hyper-parameters as\nthe original BERT model but\nwith different random seeds, which causes varia... | [
"TAGS\n#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_3 #multiberts-seed_3-step_20k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 20k\n\nMultiBERTs is a collection of checkpoints a... |
null | transformers |
# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 300k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://github.com/google-research/bert) but
with differen... | {"language": "en", "license": "apache-2.0", "tags": ["multiberts", "multiberts-seed_3", "multiberts-seed_3-step_300k"]} | google/multiberts-seed_3-step_300k | null | [
"transformers",
"pytorch",
"tf",
"bert",
"pretraining",
"multiberts",
"multiberts-seed_3",
"multiberts-seed_3-step_300k",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2106.16163",
"1908.08962"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_3 #multiberts-seed_3-step_300k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us
|
# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 300k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
the original BERT model but
with different random seeds, which causes variations in ... | [
"# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 300k\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT. We provide 25 BERT-base models trained with\nsimilar hyper-parameters as\nthe original BERT model but\nwith different random seeds, which causes vari... | [
"TAGS\n#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_3 #multiberts-seed_3-step_300k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 300k\n\nMultiBERTs is a collection of checkpoints... |
null | transformers |
# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 400k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://github.com/google-research/bert) but
with differen... | {"language": "en", "license": "apache-2.0", "tags": ["multiberts", "multiberts-seed_3", "multiberts-seed_3-step_400k"]} | google/multiberts-seed_3-step_400k | null | [
"transformers",
"pytorch",
"tf",
"bert",
"pretraining",
"multiberts",
"multiberts-seed_3",
"multiberts-seed_3-step_400k",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2106.16163",
"1908.08962"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_3 #multiberts-seed_3-step_400k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us
|
# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 400k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
the original BERT model but
with different random seeds, which causes variations in ... | [
"# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 400k\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT. We provide 25 BERT-base models trained with\nsimilar hyper-parameters as\nthe original BERT model but\nwith different random seeds, which causes vari... | [
"TAGS\n#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_3 #multiberts-seed_3-step_400k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 400k\n\nMultiBERTs is a collection of checkpoints... |
null | transformers |
# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 40k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://github.com/google-research/bert) but
with different... | {"language": "en", "license": "apache-2.0", "tags": ["multiberts", "multiberts-seed_3", "multiberts-seed_3-step_40k"]} | google/multiberts-seed_3-step_40k | null | [
"transformers",
"pytorch",
"tf",
"bert",
"pretraining",
"multiberts",
"multiberts-seed_3",
"multiberts-seed_3-step_40k",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2106.16163",
"1908.08962"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_3 #multiberts-seed_3-step_40k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us
|
# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 40k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
the original BERT model but
with different random seeds, which causes variations in t... | [
"# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 40k\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT. We provide 25 BERT-base models trained with\nsimilar hyper-parameters as\nthe original BERT model but\nwith different random seeds, which causes varia... | [
"TAGS\n#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_3 #multiberts-seed_3-step_40k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 40k\n\nMultiBERTs is a collection of checkpoints a... |
null | transformers |
# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 500k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://github.com/google-research/bert) but
with differen... | {"language": "en", "license": "apache-2.0", "tags": ["multiberts", "multiberts-seed_3", "multiberts-seed_3-step_500k"]} | google/multiberts-seed_3-step_500k | null | [
"transformers",
"pytorch",
"tf",
"bert",
"pretraining",
"multiberts",
"multiberts-seed_3",
"multiberts-seed_3-step_500k",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2106.16163",
"1908.08962"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_3 #multiberts-seed_3-step_500k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us
|
# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 500k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
the original BERT model but
with different random seeds, which causes variations in ... | [
"# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 500k\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT. We provide 25 BERT-base models trained with\nsimilar hyper-parameters as\nthe original BERT model but\nwith different random seeds, which causes vari... | [
"TAGS\n#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_3 #multiberts-seed_3-step_500k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 500k\n\nMultiBERTs is a collection of checkpoints... |
null | transformers |
# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 600k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://github.com/google-research/bert) but
with differen... | {"language": "en", "license": "apache-2.0", "tags": ["multiberts", "multiberts-seed_3", "multiberts-seed_3-step_600k"]} | google/multiberts-seed_3-step_600k | null | [
"transformers",
"pytorch",
"tf",
"bert",
"pretraining",
"multiberts",
"multiberts-seed_3",
"multiberts-seed_3-step_600k",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2106.16163",
"1908.08962"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_3 #multiberts-seed_3-step_600k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us
|
# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 600k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
the original BERT model but
with different random seeds, which causes variations in ... | [
"# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 600k\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT. We provide 25 BERT-base models trained with\nsimilar hyper-parameters as\nthe original BERT model but\nwith different random seeds, which causes vari... | [
"TAGS\n#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_3 #multiberts-seed_3-step_600k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 600k\n\nMultiBERTs is a collection of checkpoints... |
null | transformers |
# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 60k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://github.com/google-research/bert) but
with different... | {"language": "en", "license": "apache-2.0", "tags": ["multiberts", "multiberts-seed_3", "multiberts-seed_3-step_60k"]} | google/multiberts-seed_3-step_60k | null | [
"transformers",
"pytorch",
"tf",
"bert",
"pretraining",
"multiberts",
"multiberts-seed_3",
"multiberts-seed_3-step_60k",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2106.16163",
"1908.08962"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_3 #multiberts-seed_3-step_60k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us
|
# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 60k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
the original BERT model but
with different random seeds, which causes variations in t... | [
"# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 60k\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT. We provide 25 BERT-base models trained with\nsimilar hyper-parameters as\nthe original BERT model but\nwith different random seeds, which causes varia... | [
"TAGS\n#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_3 #multiberts-seed_3-step_60k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 60k\n\nMultiBERTs is a collection of checkpoints a... |
null | transformers |
# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 700k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://github.com/google-research/bert) but
with differen... | {"language": "en", "license": "apache-2.0", "tags": ["multiberts", "multiberts-seed_3", "multiberts-seed_3-step_700k"]} | google/multiberts-seed_3-step_700k | null | [
"transformers",
"pytorch",
"tf",
"bert",
"pretraining",
"multiberts",
"multiberts-seed_3",
"multiberts-seed_3-step_700k",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2106.16163",
"1908.08962"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_3 #multiberts-seed_3-step_700k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us
|
# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 700k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
the original BERT model but
with different random seeds, which causes variations in ... | [
"# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 700k\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT. We provide 25 BERT-base models trained with\nsimilar hyper-parameters as\nthe original BERT model but\nwith different random seeds, which causes vari... | [
"TAGS\n#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_3 #multiberts-seed_3-step_700k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 700k\n\nMultiBERTs is a collection of checkpoints... |
null | transformers |
# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 800k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://github.com/google-research/bert) but
with differen... | {"language": "en", "license": "apache-2.0", "tags": ["multiberts", "multiberts-seed_3", "multiberts-seed_3-step_800k"]} | google/multiberts-seed_3-step_800k | null | [
"transformers",
"pytorch",
"tf",
"bert",
"pretraining",
"multiberts",
"multiberts-seed_3",
"multiberts-seed_3-step_800k",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2106.16163",
"1908.08962"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_3 #multiberts-seed_3-step_800k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us
|
# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 800k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
the original BERT model but
with different random seeds, which causes variations in ... | [
"# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 800k\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT. We provide 25 BERT-base models trained with\nsimilar hyper-parameters as\nthe original BERT model but\nwith different random seeds, which causes vari... | [
"TAGS\n#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_3 #multiberts-seed_3-step_800k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 800k\n\nMultiBERTs is a collection of checkpoints... |
null | transformers |
# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 80k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://github.com/google-research/bert) but
with different... | {"language": "en", "license": "apache-2.0", "tags": ["multiberts", "multiberts-seed_3", "multiberts-seed_3-step_80k"]} | google/multiberts-seed_3-step_80k | null | [
"transformers",
"pytorch",
"tf",
"bert",
"pretraining",
"multiberts",
"multiberts-seed_3",
"multiberts-seed_3-step_80k",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2106.16163",
"1908.08962"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_3 #multiberts-seed_3-step_80k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us
|
# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 80k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
the original BERT model but
with different random seeds, which causes variations in t... | [
"# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 80k\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT. We provide 25 BERT-base models trained with\nsimilar hyper-parameters as\nthe original BERT model but\nwith different random seeds, which causes varia... | [
"TAGS\n#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_3 #multiberts-seed_3-step_80k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 80k\n\nMultiBERTs is a collection of checkpoints a... |
null | transformers |
# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 900k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://github.com/google-research/bert) but
with differen... | {"language": "en", "license": "apache-2.0", "tags": ["multiberts", "multiberts-seed_3", "multiberts-seed_3-step_900k"]} | google/multiberts-seed_3-step_900k | null | [
"transformers",
"pytorch",
"tf",
"bert",
"pretraining",
"multiberts",
"multiberts-seed_3",
"multiberts-seed_3-step_900k",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2106.16163",
"1908.08962"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_3 #multiberts-seed_3-step_900k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us
|
# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 900k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
the original BERT model but
with different random seeds, which causes variations in ... | [
"# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 900k\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT. We provide 25 BERT-base models trained with\nsimilar hyper-parameters as\nthe original BERT model but\nwith different random seeds, which causes vari... | [
"TAGS\n#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_3 #multiberts-seed_3-step_900k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# MultiBERTs, Intermediate Checkpoint - Seed 3, Step 900k\n\nMultiBERTs is a collection of checkpoints... |
null | transformers |
# MultiBERTs - Seed 3
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://github.com/google-research/bert) but
with different random seeds, which causes variati... | {"language": "en", "license": "apache-2.0", "tags": ["multiberts", "multiberts-seed_3"]} | google/multiberts-seed_3 | null | [
"transformers",
"pytorch",
"tf",
"bert",
"pretraining",
"multiberts",
"multiberts-seed_3",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2106.16163",
"1908.08962"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_3 #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us
|
# MultiBERTs - Seed 3
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
the original BERT model but
with different random seeds, which causes variations in the initial weights and order of
tra... | [
"# MultiBERTs - Seed 3\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT. We provide 25 BERT-base models trained with\nsimilar hyper-parameters as\nthe original BERT model but\nwith different random seeds, which causes variations in the initial weights and or... | [
"TAGS\n#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_3 #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# MultiBERTs - Seed 3\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT. W... |
null | transformers |
# MultiBERTs, Intermediate Checkpoint - Seed 4, Step 0k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://github.com/google-research/bert) but
with different ... | {"language": "en", "license": "apache-2.0", "tags": ["multiberts", "multiberts-seed_4", "multiberts-seed_4-step_0k"]} | google/multiberts-seed_4-step_0k | null | [
"transformers",
"pytorch",
"tf",
"bert",
"pretraining",
"multiberts",
"multiberts-seed_4",
"multiberts-seed_4-step_0k",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2106.16163",
"1908.08962"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_4 #multiberts-seed_4-step_0k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us
|
# MultiBERTs, Intermediate Checkpoint - Seed 4, Step 0k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
the original BERT model but
with different random seeds, which causes variations in th... | [
"# MultiBERTs, Intermediate Checkpoint - Seed 4, Step 0k\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT. We provide 25 BERT-base models trained with\nsimilar hyper-parameters as\nthe original BERT model but\nwith different random seeds, which causes variat... | [
"TAGS\n#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_4 #multiberts-seed_4-step_0k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# MultiBERTs, Intermediate Checkpoint - Seed 4, Step 0k\n\nMultiBERTs is a collection of checkpoints and... |
null | transformers |
# MultiBERTs, Intermediate Checkpoint - Seed 4, Step 1000k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://github.com/google-research/bert) but
with differe... | {"language": "en", "license": "apache-2.0", "tags": ["multiberts", "multiberts-seed_4", "multiberts-seed_4-step_1000k"]} | google/multiberts-seed_4-step_1000k | null | [
"transformers",
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"tf",
"bert",
"pretraining",
"multiberts",
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"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2106.16163",
"1908.08962"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_4 #multiberts-seed_4-step_1000k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us
|
# MultiBERTs, Intermediate Checkpoint - Seed 4, Step 1000k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
the original BERT model but
with different random seeds, which causes variations in... | [
"# MultiBERTs, Intermediate Checkpoint - Seed 4, Step 1000k\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT. We provide 25 BERT-base models trained with\nsimilar hyper-parameters as\nthe original BERT model but\nwith different random seeds, which causes var... | [
"TAGS\n#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_4 #multiberts-seed_4-step_1000k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# MultiBERTs, Intermediate Checkpoint - Seed 4, Step 1000k\n\nMultiBERTs is a collection of checkpoin... |
null | transformers |
# MultiBERTs, Intermediate Checkpoint - Seed 4, Step 100k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://github.com/google-research/bert) but
with differen... | {"language": "en", "license": "apache-2.0", "tags": ["multiberts", "multiberts-seed_4", "multiberts-seed_4-step_100k"]} | google/multiberts-seed_4-step_100k | null | [
"transformers",
"pytorch",
"tf",
"bert",
"pretraining",
"multiberts",
"multiberts-seed_4",
"multiberts-seed_4-step_100k",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2106.16163",
"1908.08962"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_4 #multiberts-seed_4-step_100k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us
|
# MultiBERTs, Intermediate Checkpoint - Seed 4, Step 100k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
the original BERT model but
with different random seeds, which causes variations in ... | [
"# MultiBERTs, Intermediate Checkpoint - Seed 4, Step 100k\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT. We provide 25 BERT-base models trained with\nsimilar hyper-parameters as\nthe original BERT model but\nwith different random seeds, which causes vari... | [
"TAGS\n#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_4 #multiberts-seed_4-step_100k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# MultiBERTs, Intermediate Checkpoint - Seed 4, Step 100k\n\nMultiBERTs is a collection of checkpoints... |
null | transformers |
# MultiBERTs, Intermediate Checkpoint - Seed 4, Step 1100k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://github.com/google-research/bert) but
with differe... | {"language": "en", "license": "apache-2.0", "tags": ["multiberts", "multiberts-seed_4", "multiberts-seed_4-step_1100k"]} | google/multiberts-seed_4-step_1100k | null | [
"transformers",
"pytorch",
"tf",
"bert",
"pretraining",
"multiberts",
"multiberts-seed_4",
"multiberts-seed_4-step_1100k",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2106.16163",
"1908.08962"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_4 #multiberts-seed_4-step_1100k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us
|
# MultiBERTs, Intermediate Checkpoint - Seed 4, Step 1100k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
the original BERT model but
with different random seeds, which causes variations in... | [
"# MultiBERTs, Intermediate Checkpoint - Seed 4, Step 1100k\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT. We provide 25 BERT-base models trained with\nsimilar hyper-parameters as\nthe original BERT model but\nwith different random seeds, which causes var... | [
"TAGS\n#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_4 #multiberts-seed_4-step_1100k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# MultiBERTs, Intermediate Checkpoint - Seed 4, Step 1100k\n\nMultiBERTs is a collection of checkpoin... |
null | transformers |
# MultiBERTs, Intermediate Checkpoint - Seed 4, Step 1200k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://github.com/google-research/bert) but
with differe... | {"language": "en", "license": "apache-2.0", "tags": ["multiberts", "multiberts-seed_4", "multiberts-seed_4-step_1200k"]} | google/multiberts-seed_4-step_1200k | null | [
"transformers",
"pytorch",
"tf",
"bert",
"pretraining",
"multiberts",
"multiberts-seed_4",
"multiberts-seed_4-step_1200k",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2106.16163",
"1908.08962"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_4 #multiberts-seed_4-step_1200k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us
|
# MultiBERTs, Intermediate Checkpoint - Seed 4, Step 1200k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
the original BERT model but
with different random seeds, which causes variations in... | [
"# MultiBERTs, Intermediate Checkpoint - Seed 4, Step 1200k\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT. We provide 25 BERT-base models trained with\nsimilar hyper-parameters as\nthe original BERT model but\nwith different random seeds, which causes var... | [
"TAGS\n#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_4 #multiberts-seed_4-step_1200k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# MultiBERTs, Intermediate Checkpoint - Seed 4, Step 1200k\n\nMultiBERTs is a collection of checkpoin... |
null | transformers |
# MultiBERTs, Intermediate Checkpoint - Seed 4, Step 120k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://github.com/google-research/bert) but
with differen... | {"language": "en", "license": "apache-2.0", "tags": ["multiberts", "multiberts-seed_4", "multiberts-seed_4-step_120k"]} | google/multiberts-seed_4-step_120k | null | [
"transformers",
"pytorch",
"tf",
"bert",
"pretraining",
"multiberts",
"multiberts-seed_4",
"multiberts-seed_4-step_120k",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2106.16163",
"1908.08962"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_4 #multiberts-seed_4-step_120k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us
|
# MultiBERTs, Intermediate Checkpoint - Seed 4, Step 120k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
the original BERT model but
with different random seeds, which causes variations in ... | [
"# MultiBERTs, Intermediate Checkpoint - Seed 4, Step 120k\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT. We provide 25 BERT-base models trained with\nsimilar hyper-parameters as\nthe original BERT model but\nwith different random seeds, which causes vari... | [
"TAGS\n#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_4 #multiberts-seed_4-step_120k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# MultiBERTs, Intermediate Checkpoint - Seed 4, Step 120k\n\nMultiBERTs is a collection of checkpoints... |
null | transformers |
# MultiBERTs, Intermediate Checkpoint - Seed 4, Step 1300k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://github.com/google-research/bert) but
with differe... | {"language": "en", "license": "apache-2.0", "tags": ["multiberts", "multiberts-seed_4", "multiberts-seed_4-step_1300k"]} | google/multiberts-seed_4-step_1300k | null | [
"transformers",
"pytorch",
"tf",
"bert",
"pretraining",
"multiberts",
"multiberts-seed_4",
"multiberts-seed_4-step_1300k",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2106.16163",
"1908.08962"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_4 #multiberts-seed_4-step_1300k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us
|
# MultiBERTs, Intermediate Checkpoint - Seed 4, Step 1300k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
the original BERT model but
with different random seeds, which causes variations in... | [
"# MultiBERTs, Intermediate Checkpoint - Seed 4, Step 1300k\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT. We provide 25 BERT-base models trained with\nsimilar hyper-parameters as\nthe original BERT model but\nwith different random seeds, which causes var... | [
"TAGS\n#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_4 #multiberts-seed_4-step_1300k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# MultiBERTs, Intermediate Checkpoint - Seed 4, Step 1300k\n\nMultiBERTs is a collection of checkpoin... |
null | transformers |
# MultiBERTs, Intermediate Checkpoint - Seed 4, Step 1400k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://github.com/google-research/bert) but
with differe... | {"language": "en", "license": "apache-2.0", "tags": ["multiberts", "multiberts-seed_4", "multiberts-seed_4-step_1400k"]} | google/multiberts-seed_4-step_1400k | null | [
"transformers",
"pytorch",
"tf",
"bert",
"pretraining",
"multiberts",
"multiberts-seed_4",
"multiberts-seed_4-step_1400k",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2106.16163",
"1908.08962"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_4 #multiberts-seed_4-step_1400k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us
|
# MultiBERTs, Intermediate Checkpoint - Seed 4, Step 1400k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
the original BERT model but
with different random seeds, which causes variations in... | [
"# MultiBERTs, Intermediate Checkpoint - Seed 4, Step 1400k\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT. We provide 25 BERT-base models trained with\nsimilar hyper-parameters as\nthe original BERT model but\nwith different random seeds, which causes var... | [
"TAGS\n#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_4 #multiberts-seed_4-step_1400k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# MultiBERTs, Intermediate Checkpoint - Seed 4, Step 1400k\n\nMultiBERTs is a collection of checkpoin... |
null | transformers |
# MultiBERTs, Intermediate Checkpoint - Seed 4, Step 140k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://github.com/google-research/bert) but
with differen... | {"language": "en", "license": "apache-2.0", "tags": ["multiberts", "multiberts-seed_4", "multiberts-seed_4-step_140k"]} | google/multiberts-seed_4-step_140k | null | [
"transformers",
"pytorch",
"tf",
"bert",
"pretraining",
"multiberts",
"multiberts-seed_4",
"multiberts-seed_4-step_140k",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2106.16163",
"1908.08962"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_4 #multiberts-seed_4-step_140k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us
|
# MultiBERTs, Intermediate Checkpoint - Seed 4, Step 140k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
the original BERT model but
with different random seeds, which causes variations in ... | [
"# MultiBERTs, Intermediate Checkpoint - Seed 4, Step 140k\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT. We provide 25 BERT-base models trained with\nsimilar hyper-parameters as\nthe original BERT model but\nwith different random seeds, which causes vari... | [
"TAGS\n#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_4 #multiberts-seed_4-step_140k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# MultiBERTs, Intermediate Checkpoint - Seed 4, Step 140k\n\nMultiBERTs is a collection of checkpoints... |
null | transformers |
# MultiBERTs, Intermediate Checkpoint - Seed 4, Step 1500k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://github.com/google-research/bert) but
with differe... | {"language": "en", "license": "apache-2.0", "tags": ["multiberts", "multiberts-seed_4", "multiberts-seed_4-step_1500k"]} | google/multiberts-seed_4-step_1500k | null | [
"transformers",
"pytorch",
"tf",
"bert",
"pretraining",
"multiberts",
"multiberts-seed_4",
"multiberts-seed_4-step_1500k",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2106.16163",
"1908.08962"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_4 #multiberts-seed_4-step_1500k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us
|
# MultiBERTs, Intermediate Checkpoint - Seed 4, Step 1500k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
the original BERT model but
with different random seeds, which causes variations in... | [
"# MultiBERTs, Intermediate Checkpoint - Seed 4, Step 1500k\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT. We provide 25 BERT-base models trained with\nsimilar hyper-parameters as\nthe original BERT model but\nwith different random seeds, which causes var... | [
"TAGS\n#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_4 #multiberts-seed_4-step_1500k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# MultiBERTs, Intermediate Checkpoint - Seed 4, Step 1500k\n\nMultiBERTs is a collection of checkpoin... |
null | transformers |
# MultiBERTs, Intermediate Checkpoint - Seed 4, Step 1600k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://github.com/google-research/bert) but
with differe... | {"language": "en", "license": "apache-2.0", "tags": ["multiberts", "multiberts-seed_4", "multiberts-seed_4-step_1600k"]} | google/multiberts-seed_4-step_1600k | null | [
"transformers",
"pytorch",
"tf",
"bert",
"pretraining",
"multiberts",
"multiberts-seed_4",
"multiberts-seed_4-step_1600k",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2106.16163",
"1908.08962"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_4 #multiberts-seed_4-step_1600k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us
|
# MultiBERTs, Intermediate Checkpoint - Seed 4, Step 1600k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
the original BERT model but
with different random seeds, which causes variations in... | [
"# MultiBERTs, Intermediate Checkpoint - Seed 4, Step 1600k\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT. We provide 25 BERT-base models trained with\nsimilar hyper-parameters as\nthe original BERT model but\nwith different random seeds, which causes var... | [
"TAGS\n#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_4 #multiberts-seed_4-step_1600k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# MultiBERTs, Intermediate Checkpoint - Seed 4, Step 1600k\n\nMultiBERTs is a collection of checkpoin... |
null | transformers |
# MultiBERTs, Intermediate Checkpoint - Seed 4, Step 160k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://github.com/google-research/bert) but
with differen... | {"language": "en", "license": "apache-2.0", "tags": ["multiberts", "multiberts-seed_4", "multiberts-seed_4-step_160k"]} | google/multiberts-seed_4-step_160k | null | [
"transformers",
"pytorch",
"tf",
"bert",
"pretraining",
"multiberts",
"multiberts-seed_4",
"multiberts-seed_4-step_160k",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2106.16163",
"1908.08962"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_4 #multiberts-seed_4-step_160k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us
|
# MultiBERTs, Intermediate Checkpoint - Seed 4, Step 160k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
the original BERT model but
with different random seeds, which causes variations in ... | [
"# MultiBERTs, Intermediate Checkpoint - Seed 4, Step 160k\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT. We provide 25 BERT-base models trained with\nsimilar hyper-parameters as\nthe original BERT model but\nwith different random seeds, which causes vari... | [
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"# MultiBERTs, Intermediate Checkpoint - Seed 4, Step 160k\n\nMultiBERTs is a collection of checkpoints... |
null | transformers |
# MultiBERTs, Intermediate Checkpoint - Seed 4, Step 1700k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://github.com/google-research/bert) but
with differe... | {"language": "en", "license": "apache-2.0", "tags": ["multiberts", "multiberts-seed_4", "multiberts-seed_4-step_1700k"]} | google/multiberts-seed_4-step_1700k | null | [
"transformers",
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"bert",
"pretraining",
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"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2106.16163",
"1908.08962"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_4 #multiberts-seed_4-step_1700k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us
|
# MultiBERTs, Intermediate Checkpoint - Seed 4, Step 1700k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
the original BERT model but
with different random seeds, which causes variations in... | [
"# MultiBERTs, Intermediate Checkpoint - Seed 4, Step 1700k\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT. We provide 25 BERT-base models trained with\nsimilar hyper-parameters as\nthe original BERT model but\nwith different random seeds, which causes var... | [
"TAGS\n#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_4 #multiberts-seed_4-step_1700k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# MultiBERTs, Intermediate Checkpoint - Seed 4, Step 1700k\n\nMultiBERTs is a collection of checkpoin... |
null | transformers |
# MultiBERTs, Intermediate Checkpoint - Seed 4, Step 1800k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://github.com/google-research/bert) but
with differe... | {"language": "en", "license": "apache-2.0", "tags": ["multiberts", "multiberts-seed_4", "multiberts-seed_4-step_1800k"]} | google/multiberts-seed_4-step_1800k | null | [
"transformers",
"pytorch",
"tf",
"bert",
"pretraining",
"multiberts",
"multiberts-seed_4",
"multiberts-seed_4-step_1800k",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2106.16163",
"1908.08962"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_4 #multiberts-seed_4-step_1800k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us
|
# MultiBERTs, Intermediate Checkpoint - Seed 4, Step 1800k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
the original BERT model but
with different random seeds, which causes variations in... | [
"# MultiBERTs, Intermediate Checkpoint - Seed 4, Step 1800k\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT. We provide 25 BERT-base models trained with\nsimilar hyper-parameters as\nthe original BERT model but\nwith different random seeds, which causes var... | [
"TAGS\n#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_4 #multiberts-seed_4-step_1800k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# MultiBERTs, Intermediate Checkpoint - Seed 4, Step 1800k\n\nMultiBERTs is a collection of checkpoin... |
null | transformers |
# MultiBERTs, Intermediate Checkpoint - Seed 4, Step 180k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://github.com/google-research/bert) but
with differen... | {"language": "en", "license": "apache-2.0", "tags": ["multiberts", "multiberts-seed_4", "multiberts-seed_4-step_180k"]} | google/multiberts-seed_4-step_180k | null | [
"transformers",
"pytorch",
"tf",
"bert",
"pretraining",
"multiberts",
"multiberts-seed_4",
"multiberts-seed_4-step_180k",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2106.16163",
"1908.08962"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_4 #multiberts-seed_4-step_180k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us
|
# MultiBERTs, Intermediate Checkpoint - Seed 4, Step 180k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
the original BERT model but
with different random seeds, which causes variations in ... | [
"# MultiBERTs, Intermediate Checkpoint - Seed 4, Step 180k\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT. We provide 25 BERT-base models trained with\nsimilar hyper-parameters as\nthe original BERT model but\nwith different random seeds, which causes vari... | [
"TAGS\n#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_4 #multiberts-seed_4-step_180k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# MultiBERTs, Intermediate Checkpoint - Seed 4, Step 180k\n\nMultiBERTs is a collection of checkpoints... |
null | transformers |
# MultiBERTs, Intermediate Checkpoint - Seed 4, Step 1900k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://github.com/google-research/bert) but
with differe... | {"language": "en", "license": "apache-2.0", "tags": ["multiberts", "multiberts-seed_4", "multiberts-seed_4-step_1900k"]} | google/multiberts-seed_4-step_1900k | null | [
"transformers",
"pytorch",
"tf",
"bert",
"pretraining",
"multiberts",
"multiberts-seed_4",
"multiberts-seed_4-step_1900k",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2106.16163",
"1908.08962"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_4 #multiberts-seed_4-step_1900k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us
|
# MultiBERTs, Intermediate Checkpoint - Seed 4, Step 1900k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
the original BERT model but
with different random seeds, which causes variations in... | [
"# MultiBERTs, Intermediate Checkpoint - Seed 4, Step 1900k\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT. We provide 25 BERT-base models trained with\nsimilar hyper-parameters as\nthe original BERT model but\nwith different random seeds, which causes var... | [
"TAGS\n#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_4 #multiberts-seed_4-step_1900k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# MultiBERTs, Intermediate Checkpoint - Seed 4, Step 1900k\n\nMultiBERTs is a collection of checkpoin... |
null | transformers |
# MultiBERTs, Intermediate Checkpoint - Seed 4, Step 2000k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://github.com/google-research/bert) but
with differe... | {"language": "en", "license": "apache-2.0", "tags": ["multiberts", "multiberts-seed_4", "multiberts-seed_4-step_2000k"]} | google/multiberts-seed_4-step_2000k | null | [
"transformers",
"pytorch",
"tf",
"bert",
"pretraining",
"multiberts",
"multiberts-seed_4",
"multiberts-seed_4-step_2000k",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2106.16163",
"1908.08962"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_4 #multiberts-seed_4-step_2000k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us
|
# MultiBERTs, Intermediate Checkpoint - Seed 4, Step 2000k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
the original BERT model but
with different random seeds, which causes variations in... | [
"# MultiBERTs, Intermediate Checkpoint - Seed 4, Step 2000k\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT. We provide 25 BERT-base models trained with\nsimilar hyper-parameters as\nthe original BERT model but\nwith different random seeds, which causes var... | [
"TAGS\n#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_4 #multiberts-seed_4-step_2000k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# MultiBERTs, Intermediate Checkpoint - Seed 4, Step 2000k\n\nMultiBERTs is a collection of checkpoin... |
null | transformers |
# MultiBERTs, Intermediate Checkpoint - Seed 4, Step 200k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://github.com/google-research/bert) but
with differen... | {"language": "en", "license": "apache-2.0", "tags": ["multiberts", "multiberts-seed_4", "multiberts-seed_4-step_200k"]} | google/multiberts-seed_4-step_200k | null | [
"transformers",
"pytorch",
"tf",
"bert",
"pretraining",
"multiberts",
"multiberts-seed_4",
"multiberts-seed_4-step_200k",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2106.16163",
"1908.08962"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_4 #multiberts-seed_4-step_200k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us
|
# MultiBERTs, Intermediate Checkpoint - Seed 4, Step 200k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
the original BERT model but
with different random seeds, which causes variations in ... | [
"# MultiBERTs, Intermediate Checkpoint - Seed 4, Step 200k\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT. We provide 25 BERT-base models trained with\nsimilar hyper-parameters as\nthe original BERT model but\nwith different random seeds, which causes vari... | [
"TAGS\n#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_4 #multiberts-seed_4-step_200k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# MultiBERTs, Intermediate Checkpoint - Seed 4, Step 200k\n\nMultiBERTs is a collection of checkpoints... |
null | transformers |
# MultiBERTs, Intermediate Checkpoint - Seed 4, Step 20k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://github.com/google-research/bert) but
with different... | {"language": "en", "license": "apache-2.0", "tags": ["multiberts", "multiberts-seed_4", "multiberts-seed_4-step_20k"]} | google/multiberts-seed_4-step_20k | null | [
"transformers",
"pytorch",
"tf",
"bert",
"pretraining",
"multiberts",
"multiberts-seed_4",
"multiberts-seed_4-step_20k",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2106.16163",
"1908.08962"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_4 #multiberts-seed_4-step_20k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us
|
# MultiBERTs, Intermediate Checkpoint - Seed 4, Step 20k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
the original BERT model but
with different random seeds, which causes variations in t... | [
"# MultiBERTs, Intermediate Checkpoint - Seed 4, Step 20k\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT. We provide 25 BERT-base models trained with\nsimilar hyper-parameters as\nthe original BERT model but\nwith different random seeds, which causes varia... | [
"TAGS\n#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_4 #multiberts-seed_4-step_20k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# MultiBERTs, Intermediate Checkpoint - Seed 4, Step 20k\n\nMultiBERTs is a collection of checkpoints a... |
null | transformers |
# MultiBERTs, Intermediate Checkpoint - Seed 4, Step 300k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://github.com/google-research/bert) but
with differen... | {"language": "en", "license": "apache-2.0", "tags": ["multiberts", "multiberts-seed_4", "multiberts-seed_4-step_300k"]} | google/multiberts-seed_4-step_300k | null | [
"transformers",
"pytorch",
"tf",
"bert",
"pretraining",
"multiberts",
"multiberts-seed_4",
"multiberts-seed_4-step_300k",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2106.16163",
"1908.08962"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_4 #multiberts-seed_4-step_300k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us
|
# MultiBERTs, Intermediate Checkpoint - Seed 4, Step 300k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
the original BERT model but
with different random seeds, which causes variations in ... | [
"# MultiBERTs, Intermediate Checkpoint - Seed 4, Step 300k\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT. We provide 25 BERT-base models trained with\nsimilar hyper-parameters as\nthe original BERT model but\nwith different random seeds, which causes vari... | [
"TAGS\n#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_4 #multiberts-seed_4-step_300k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# MultiBERTs, Intermediate Checkpoint - Seed 4, Step 300k\n\nMultiBERTs is a collection of checkpoints... |
null | transformers |
# MultiBERTs, Intermediate Checkpoint - Seed 4, Step 400k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://github.com/google-research/bert) but
with differen... | {"language": "en", "license": "apache-2.0", "tags": ["multiberts", "multiberts-seed_4", "multiberts-seed_4-step_400k"]} | google/multiberts-seed_4-step_400k | null | [
"transformers",
"pytorch",
"tf",
"bert",
"pretraining",
"multiberts",
"multiberts-seed_4",
"multiberts-seed_4-step_400k",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2106.16163",
"1908.08962"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_4 #multiberts-seed_4-step_400k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us
|
# MultiBERTs, Intermediate Checkpoint - Seed 4, Step 400k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
the original BERT model but
with different random seeds, which causes variations in ... | [
"# MultiBERTs, Intermediate Checkpoint - Seed 4, Step 400k\n\nMultiBERTs is a collection of checkpoints and a statistical library to support\nrobust research on BERT. We provide 25 BERT-base models trained with\nsimilar hyper-parameters as\nthe original BERT model but\nwith different random seeds, which causes vari... | [
"TAGS\n#transformers #pytorch #tf #bert #pretraining #multiberts #multiberts-seed_4 #multiberts-seed_4-step_400k #en #arxiv-2106.16163 #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# MultiBERTs, Intermediate Checkpoint - Seed 4, Step 400k\n\nMultiBERTs is a collection of checkpoints... |
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