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fill-mask | transformers |
# RoBERTa, Intermediate Checkpoint - Epoch 28
This model is part of our reimplementation of the [RoBERTa model](https://arxiv.org/abs/1907.11692),
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randoml... | {"language": "en", "license": "mit", "tags": ["roberta-base", "roberta-base-epoch_28"], "datasets": ["wikipedia", "bookcorpus"]} | yanaiela/roberta-base-epoch_28 | null | [
"transformers",
"pytorch",
"roberta",
"fill-mask",
"roberta-base",
"roberta-base-epoch_28",
"en",
"dataset:wikipedia",
"dataset:bookcorpus",
"arxiv:1907.11692",
"arxiv:2207.14251",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-28T16:11:20+00:00 | [
"1907.11692",
"2207.14251"
] | [
"en"
] | TAGS
#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_28 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us
|
# RoBERTa, Intermediate Checkpoint - Epoch 28
This model is part of our reimplementation of the RoBERTa model,
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randomly initialized weights before the tra... | [
"# RoBERTa, Intermediate Checkpoint - Epoch 28\n\nThis model is part of our reimplementation of the RoBERTa model, \ntrained on Wikipedia and the Book Corpus only.\nWe train this model for almost 100K steps, corresponding to 83 epochs.\nWe provide the 84 checkpoints (including the randomly initialized weights befor... | [
"TAGS\n#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_28 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us \n",
"# RoBERTa, Intermediate Checkpoint - Epoch 28\n\nThis model is part of our... |
fill-mask | transformers |
# RoBERTa, Intermediate Checkpoint - Epoch 29
This model is part of our reimplementation of the [RoBERTa model](https://arxiv.org/abs/1907.11692),
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randoml... | {"language": "en", "license": "mit", "tags": ["roberta-base", "roberta-base-epoch_29"], "datasets": ["wikipedia", "bookcorpus"]} | yanaiela/roberta-base-epoch_29 | null | [
"transformers",
"pytorch",
"roberta",
"fill-mask",
"roberta-base",
"roberta-base-epoch_29",
"en",
"dataset:wikipedia",
"dataset:bookcorpus",
"arxiv:1907.11692",
"arxiv:2207.14251",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-28T16:12:07+00:00 | [
"1907.11692",
"2207.14251"
] | [
"en"
] | TAGS
#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_29 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us
|
# RoBERTa, Intermediate Checkpoint - Epoch 29
This model is part of our reimplementation of the RoBERTa model,
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randomly initialized weights before the tra... | [
"# RoBERTa, Intermediate Checkpoint - Epoch 29\n\nThis model is part of our reimplementation of the RoBERTa model, \ntrained on Wikipedia and the Book Corpus only.\nWe train this model for almost 100K steps, corresponding to 83 epochs.\nWe provide the 84 checkpoints (including the randomly initialized weights befor... | [
"TAGS\n#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_29 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us \n",
"# RoBERTa, Intermediate Checkpoint - Epoch 29\n\nThis model is part of our... |
fill-mask | transformers |
# RoBERTa, Intermediate Checkpoint - Epoch 30
This model is part of our reimplementation of the [RoBERTa model](https://arxiv.org/abs/1907.11692),
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randoml... | {"language": "en", "license": "mit", "tags": ["roberta-base", "roberta-base-epoch_30"], "datasets": ["wikipedia", "bookcorpus"]} | yanaiela/roberta-base-epoch_30 | null | [
"transformers",
"pytorch",
"roberta",
"fill-mask",
"roberta-base",
"roberta-base-epoch_30",
"en",
"dataset:wikipedia",
"dataset:bookcorpus",
"arxiv:1907.11692",
"arxiv:2207.14251",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-28T16:13:21+00:00 | [
"1907.11692",
"2207.14251"
] | [
"en"
] | TAGS
#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_30 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us
|
# RoBERTa, Intermediate Checkpoint - Epoch 30
This model is part of our reimplementation of the RoBERTa model,
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randomly initialized weights before the tra... | [
"# RoBERTa, Intermediate Checkpoint - Epoch 30\n\nThis model is part of our reimplementation of the RoBERTa model, \ntrained on Wikipedia and the Book Corpus only.\nWe train this model for almost 100K steps, corresponding to 83 epochs.\nWe provide the 84 checkpoints (including the randomly initialized weights befor... | [
"TAGS\n#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_30 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us \n",
"# RoBERTa, Intermediate Checkpoint - Epoch 30\n\nThis model is part of our... |
fill-mask | transformers |
# RoBERTa, Intermediate Checkpoint - Epoch 31
This model is part of our reimplementation of the [RoBERTa model](https://arxiv.org/abs/1907.11692),
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randoml... | {"language": "en", "license": "mit", "tags": ["roberta-base", "roberta-base-epoch_31"], "datasets": ["wikipedia", "bookcorpus"]} | yanaiela/roberta-base-epoch_31 | null | [
"transformers",
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"roberta",
"fill-mask",
"roberta-base",
"roberta-base-epoch_31",
"en",
"dataset:wikipedia",
"dataset:bookcorpus",
"arxiv:1907.11692",
"arxiv:2207.14251",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-28T16:14:05+00:00 | [
"1907.11692",
"2207.14251"
] | [
"en"
] | TAGS
#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_31 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us
|
# RoBERTa, Intermediate Checkpoint - Epoch 31
This model is part of our reimplementation of the RoBERTa model,
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randomly initialized weights before the tra... | [
"# RoBERTa, Intermediate Checkpoint - Epoch 31\n\nThis model is part of our reimplementation of the RoBERTa model, \ntrained on Wikipedia and the Book Corpus only.\nWe train this model for almost 100K steps, corresponding to 83 epochs.\nWe provide the 84 checkpoints (including the randomly initialized weights befor... | [
"TAGS\n#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_31 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us \n",
"# RoBERTa, Intermediate Checkpoint - Epoch 31\n\nThis model is part of our... |
fill-mask | transformers |
# RoBERTa, Intermediate Checkpoint - Epoch 32
This model is part of our reimplementation of the [RoBERTa model](https://arxiv.org/abs/1907.11692),
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randoml... | {"language": "en", "license": "mit", "tags": ["roberta-base", "roberta-base-epoch_32"], "datasets": ["wikipedia", "bookcorpus"]} | yanaiela/roberta-base-epoch_32 | null | [
"transformers",
"pytorch",
"roberta",
"fill-mask",
"roberta-base",
"roberta-base-epoch_32",
"en",
"dataset:wikipedia",
"dataset:bookcorpus",
"arxiv:1907.11692",
"arxiv:2207.14251",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-28T16:14:49+00:00 | [
"1907.11692",
"2207.14251"
] | [
"en"
] | TAGS
#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_32 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us
|
# RoBERTa, Intermediate Checkpoint - Epoch 32
This model is part of our reimplementation of the RoBERTa model,
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randomly initialized weights before the tra... | [
"# RoBERTa, Intermediate Checkpoint - Epoch 32\n\nThis model is part of our reimplementation of the RoBERTa model, \ntrained on Wikipedia and the Book Corpus only.\nWe train this model for almost 100K steps, corresponding to 83 epochs.\nWe provide the 84 checkpoints (including the randomly initialized weights befor... | [
"TAGS\n#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_32 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us \n",
"# RoBERTa, Intermediate Checkpoint - Epoch 32\n\nThis model is part of our... |
fill-mask | transformers |
# RoBERTa, Intermediate Checkpoint - Epoch 33
This model is part of our reimplementation of the [RoBERTa model](https://arxiv.org/abs/1907.11692),
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randoml... | {"language": "en", "license": "mit", "tags": ["roberta-base", "roberta-base-epoch_33"], "datasets": ["wikipedia", "bookcorpus"]} | yanaiela/roberta-base-epoch_33 | null | [
"transformers",
"pytorch",
"roberta",
"fill-mask",
"roberta-base",
"roberta-base-epoch_33",
"en",
"dataset:wikipedia",
"dataset:bookcorpus",
"arxiv:1907.11692",
"arxiv:2207.14251",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-28T16:15:37+00:00 | [
"1907.11692",
"2207.14251"
] | [
"en"
] | TAGS
#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_33 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us
|
# RoBERTa, Intermediate Checkpoint - Epoch 33
This model is part of our reimplementation of the RoBERTa model,
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randomly initialized weights before the tra... | [
"# RoBERTa, Intermediate Checkpoint - Epoch 33\n\nThis model is part of our reimplementation of the RoBERTa model, \ntrained on Wikipedia and the Book Corpus only.\nWe train this model for almost 100K steps, corresponding to 83 epochs.\nWe provide the 84 checkpoints (including the randomly initialized weights befor... | [
"TAGS\n#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_33 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us \n",
"# RoBERTa, Intermediate Checkpoint - Epoch 33\n\nThis model is part of our... |
fill-mask | transformers |
# RoBERTa, Intermediate Checkpoint - Epoch 34
This model is part of our reimplementation of the [RoBERTa model](https://arxiv.org/abs/1907.11692),
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randoml... | {"language": "en", "license": "mit", "tags": ["roberta-base", "roberta-base-epoch_34"], "datasets": ["wikipedia", "bookcorpus"]} | yanaiela/roberta-base-epoch_34 | null | [
"transformers",
"pytorch",
"roberta",
"fill-mask",
"roberta-base",
"roberta-base-epoch_34",
"en",
"dataset:wikipedia",
"dataset:bookcorpus",
"arxiv:1907.11692",
"arxiv:2207.14251",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-28T16:16:23+00:00 | [
"1907.11692",
"2207.14251"
] | [
"en"
] | TAGS
#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_34 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us
|
# RoBERTa, Intermediate Checkpoint - Epoch 34
This model is part of our reimplementation of the RoBERTa model,
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randomly initialized weights before the tra... | [
"# RoBERTa, Intermediate Checkpoint - Epoch 34\n\nThis model is part of our reimplementation of the RoBERTa model, \ntrained on Wikipedia and the Book Corpus only.\nWe train this model for almost 100K steps, corresponding to 83 epochs.\nWe provide the 84 checkpoints (including the randomly initialized weights befor... | [
"TAGS\n#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_34 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us \n",
"# RoBERTa, Intermediate Checkpoint - Epoch 34\n\nThis model is part of our... |
null | keras |
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
| name | learning_rate | decay | rho | momentu... | {"library_name": "keras"} | Ravindra001/conv_bn | null | [
"keras",
"region:us"
] | null | 2022-07-28T16:17:00+00:00 | [] | [] | TAGS
#keras #region-us
| Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More information needed
Training and evaluation data
----------------------------
More information needed
Training procedure
------------------
### Training hyperparameters
The following h... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n\nModel Plot\n----------\n\n\n\nView Model Plot\n!Model Image"
] | [
"TAGS\n#keras #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n\nModel Plot\n----------\n\n\n\nView Model Plot\n!Model Image"
] |
fill-mask | transformers |
# RoBERTa, Intermediate Checkpoint - Epoch 35
This model is part of our reimplementation of the [RoBERTa model](https://arxiv.org/abs/1907.11692),
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randoml... | {"language": "en", "license": "mit", "tags": ["roberta-base", "roberta-base-epoch_35"], "datasets": ["wikipedia", "bookcorpus"]} | yanaiela/roberta-base-epoch_35 | null | [
"transformers",
"pytorch",
"roberta",
"fill-mask",
"roberta-base",
"roberta-base-epoch_35",
"en",
"dataset:wikipedia",
"dataset:bookcorpus",
"arxiv:1907.11692",
"arxiv:2207.14251",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-28T16:17:09+00:00 | [
"1907.11692",
"2207.14251"
] | [
"en"
] | TAGS
#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_35 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us
|
# RoBERTa, Intermediate Checkpoint - Epoch 35
This model is part of our reimplementation of the RoBERTa model,
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randomly initialized weights before the tra... | [
"# RoBERTa, Intermediate Checkpoint - Epoch 35\n\nThis model is part of our reimplementation of the RoBERTa model, \ntrained on Wikipedia and the Book Corpus only.\nWe train this model for almost 100K steps, corresponding to 83 epochs.\nWe provide the 84 checkpoints (including the randomly initialized weights befor... | [
"TAGS\n#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_35 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us \n",
"# RoBERTa, Intermediate Checkpoint - Epoch 35\n\nThis model is part of our... |
fill-mask | transformers |
# RoBERTa, Intermediate Checkpoint - Epoch 36
This model is part of our reimplementation of the [RoBERTa model](https://arxiv.org/abs/1907.11692),
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randoml... | {"language": "en", "license": "mit", "tags": ["roberta-base", "roberta-base-epoch_36"], "datasets": ["wikipedia", "bookcorpus"]} | yanaiela/roberta-base-epoch_36 | null | [
"transformers",
"pytorch",
"roberta",
"fill-mask",
"roberta-base",
"roberta-base-epoch_36",
"en",
"dataset:wikipedia",
"dataset:bookcorpus",
"arxiv:1907.11692",
"arxiv:2207.14251",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-28T16:17:50+00:00 | [
"1907.11692",
"2207.14251"
] | [
"en"
] | TAGS
#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_36 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us
|
# RoBERTa, Intermediate Checkpoint - Epoch 36
This model is part of our reimplementation of the RoBERTa model,
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randomly initialized weights before the tra... | [
"# RoBERTa, Intermediate Checkpoint - Epoch 36\n\nThis model is part of our reimplementation of the RoBERTa model, \ntrained on Wikipedia and the Book Corpus only.\nWe train this model for almost 100K steps, corresponding to 83 epochs.\nWe provide the 84 checkpoints (including the randomly initialized weights befor... | [
"TAGS\n#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_36 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us \n",
"# RoBERTa, Intermediate Checkpoint - Epoch 36\n\nThis model is part of our... |
text-classification | transformers |
<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->
# dspa
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dat... | {"license": "apache-2.0", "tags": ["generated_from_keras_callback"], "model-index": [{"name": "dspa", "results": []}]} | amirthaa/dspa | null | [
"transformers",
"tf",
"distilbert",
"text-classification",
"generated_from_keras_callback",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-07-28T16:18:27+00:00 | [] | [] | TAGS
#transformers #tf #distilbert #text-classification #generated_from_keras_callback #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us
| dspa
====
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset.
It achieves the following results on the evaluation set:
* Train Loss: 0.6069
* Validation Loss: 0.6854
* Epoch: 1
Model description
-----------------
More information needed
Intended uses & limitations
------------... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* optimizer: {'name': 'Adam', 'learning\\_rate': {'class\\_name': 'PolynomialDecay', 'config': {'initial\\_learning\\_rate': 2e-05, 'decay\\_steps': 142110, 'end\\_learning\\_rate': 0.0, 'power': 1.0, 'cycle': False, 'n... | [
"TAGS\n#transformers #tf #distilbert #text-classification #generated_from_keras_callback #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* optimizer: {'name': 'Adam', 'learni... |
fill-mask | transformers |
# RoBERTa, Intermediate Checkpoint - Epoch 37
This model is part of our reimplementation of the [RoBERTa model](https://arxiv.org/abs/1907.11692),
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randoml... | {"language": "en", "license": "mit", "tags": ["roberta-base", "roberta-base-epoch_37"], "datasets": ["wikipedia", "bookcorpus"]} | yanaiela/roberta-base-epoch_37 | null | [
"transformers",
"pytorch",
"roberta",
"fill-mask",
"roberta-base",
"roberta-base-epoch_37",
"en",
"dataset:wikipedia",
"dataset:bookcorpus",
"arxiv:1907.11692",
"arxiv:2207.14251",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-28T16:18:36+00:00 | [
"1907.11692",
"2207.14251"
] | [
"en"
] | TAGS
#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_37 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us
|
# RoBERTa, Intermediate Checkpoint - Epoch 37
This model is part of our reimplementation of the RoBERTa model,
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randomly initialized weights before the tra... | [
"# RoBERTa, Intermediate Checkpoint - Epoch 37\n\nThis model is part of our reimplementation of the RoBERTa model, \ntrained on Wikipedia and the Book Corpus only.\nWe train this model for almost 100K steps, corresponding to 83 epochs.\nWe provide the 84 checkpoints (including the randomly initialized weights befor... | [
"TAGS\n#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_37 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us \n",
"# RoBERTa, Intermediate Checkpoint - Epoch 37\n\nThis model is part of our... |
fill-mask | transformers |
# RoBERTa, Intermediate Checkpoint - Epoch 38
This model is part of our reimplementation of the [RoBERTa model](https://arxiv.org/abs/1907.11692),
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randoml... | {"language": "en", "license": "mit", "tags": ["roberta-base", "roberta-base-epoch_38"], "datasets": ["wikipedia", "bookcorpus"]} | yanaiela/roberta-base-epoch_38 | null | [
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"license:mit",
"autotrain_compatible",
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"region:us"
] | null | 2022-07-28T16:19:21+00:00 | [
"1907.11692",
"2207.14251"
] | [
"en"
] | TAGS
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|
# RoBERTa, Intermediate Checkpoint - Epoch 38
This model is part of our reimplementation of the RoBERTa model,
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randomly initialized weights before the tra... | [
"# RoBERTa, Intermediate Checkpoint - Epoch 38\n\nThis model is part of our reimplementation of the RoBERTa model, \ntrained on Wikipedia and the Book Corpus only.\nWe train this model for almost 100K steps, corresponding to 83 epochs.\nWe provide the 84 checkpoints (including the randomly initialized weights befor... | [
"TAGS\n#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_38 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us \n",
"# RoBERTa, Intermediate Checkpoint - Epoch 38\n\nThis model is part of our... |
fill-mask | transformers |
# RoBERTa, Intermediate Checkpoint - Epoch 39
This model is part of our reimplementation of the [RoBERTa model](https://arxiv.org/abs/1907.11692),
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randoml... | {"language": "en", "license": "mit", "tags": ["roberta-base", "roberta-base-epoch_39"], "datasets": ["wikipedia", "bookcorpus"]} | yanaiela/roberta-base-epoch_39 | null | [
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"arxiv:1907.11692",
"arxiv:2207.14251",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-28T16:20:23+00:00 | [
"1907.11692",
"2207.14251"
] | [
"en"
] | TAGS
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|
# RoBERTa, Intermediate Checkpoint - Epoch 39
This model is part of our reimplementation of the RoBERTa model,
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randomly initialized weights before the tra... | [
"# RoBERTa, Intermediate Checkpoint - Epoch 39\n\nThis model is part of our reimplementation of the RoBERTa model, \ntrained on Wikipedia and the Book Corpus only.\nWe train this model for almost 100K steps, corresponding to 83 epochs.\nWe provide the 84 checkpoints (including the randomly initialized weights befor... | [
"TAGS\n#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_39 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us \n",
"# RoBERTa, Intermediate Checkpoint - Epoch 39\n\nThis model is part of our... |
fill-mask | transformers |
# RoBERTa, Intermediate Checkpoint - Epoch 40
This model is part of our reimplementation of the [RoBERTa model](https://arxiv.org/abs/1907.11692),
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randoml... | {"language": "en", "license": "mit", "tags": ["roberta-base", "roberta-base-epoch_40"], "datasets": ["wikipedia", "bookcorpus"]} | yanaiela/roberta-base-epoch_40 | null | [
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"arxiv:1907.11692",
"arxiv:2207.14251",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-28T16:21:04+00:00 | [
"1907.11692",
"2207.14251"
] | [
"en"
] | TAGS
#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_40 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us
|
# RoBERTa, Intermediate Checkpoint - Epoch 40
This model is part of our reimplementation of the RoBERTa model,
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randomly initialized weights before the tra... | [
"# RoBERTa, Intermediate Checkpoint - Epoch 40\n\nThis model is part of our reimplementation of the RoBERTa model, \ntrained on Wikipedia and the Book Corpus only.\nWe train this model for almost 100K steps, corresponding to 83 epochs.\nWe provide the 84 checkpoints (including the randomly initialized weights befor... | [
"TAGS\n#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_40 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us \n",
"# RoBERTa, Intermediate Checkpoint - Epoch 40\n\nThis model is part of our... |
fill-mask | transformers |
# RoBERTa, Intermediate Checkpoint - Epoch 41
This model is part of our reimplementation of the [RoBERTa model](https://arxiv.org/abs/1907.11692),
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randoml... | {"language": "en", "license": "mit", "tags": ["roberta-base", "roberta-base-epoch_41"], "datasets": ["wikipedia", "bookcorpus"]} | yanaiela/roberta-base-epoch_41 | null | [
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"fill-mask",
"roberta-base",
"roberta-base-epoch_41",
"en",
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"arxiv:1907.11692",
"arxiv:2207.14251",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-28T16:21:50+00:00 | [
"1907.11692",
"2207.14251"
] | [
"en"
] | TAGS
#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_41 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us
|
# RoBERTa, Intermediate Checkpoint - Epoch 41
This model is part of our reimplementation of the RoBERTa model,
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randomly initialized weights before the tra... | [
"# RoBERTa, Intermediate Checkpoint - Epoch 41\n\nThis model is part of our reimplementation of the RoBERTa model, \ntrained on Wikipedia and the Book Corpus only.\nWe train this model for almost 100K steps, corresponding to 83 epochs.\nWe provide the 84 checkpoints (including the randomly initialized weights befor... | [
"TAGS\n#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_41 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us \n",
"# RoBERTa, Intermediate Checkpoint - Epoch 41\n\nThis model is part of our... |
fill-mask | transformers |
# RoBERTa, Intermediate Checkpoint - Epoch 42
This model is part of our reimplementation of the [RoBERTa model](https://arxiv.org/abs/1907.11692),
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randoml... | {"language": "en", "license": "mit", "tags": ["roberta-base", "roberta-base-epoch_42"], "datasets": ["wikipedia", "bookcorpus"]} | yanaiela/roberta-base-epoch_42 | null | [
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"roberta",
"fill-mask",
"roberta-base",
"roberta-base-epoch_42",
"en",
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"dataset:bookcorpus",
"arxiv:1907.11692",
"arxiv:2207.14251",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-28T16:22:35+00:00 | [
"1907.11692",
"2207.14251"
] | [
"en"
] | TAGS
#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_42 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us
|
# RoBERTa, Intermediate Checkpoint - Epoch 42
This model is part of our reimplementation of the RoBERTa model,
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randomly initialized weights before the tra... | [
"# RoBERTa, Intermediate Checkpoint - Epoch 42\n\nThis model is part of our reimplementation of the RoBERTa model, \ntrained on Wikipedia and the Book Corpus only.\nWe train this model for almost 100K steps, corresponding to 83 epochs.\nWe provide the 84 checkpoints (including the randomly initialized weights befor... | [
"TAGS\n#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_42 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us \n",
"# RoBERTa, Intermediate Checkpoint - Epoch 42\n\nThis model is part of our... |
fill-mask | transformers |
# RoBERTa, Intermediate Checkpoint - Epoch 43
This model is part of our reimplementation of the [RoBERTa model](https://arxiv.org/abs/1907.11692),
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randoml... | {"language": "en", "license": "mit", "tags": ["roberta-base", "roberta-base-epoch_43"], "datasets": ["wikipedia", "bookcorpus"]} | yanaiela/roberta-base-epoch_43 | null | [
"transformers",
"pytorch",
"roberta",
"fill-mask",
"roberta-base",
"roberta-base-epoch_43",
"en",
"dataset:wikipedia",
"dataset:bookcorpus",
"arxiv:1907.11692",
"arxiv:2207.14251",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-28T16:23:18+00:00 | [
"1907.11692",
"2207.14251"
] | [
"en"
] | TAGS
#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_43 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us
|
# RoBERTa, Intermediate Checkpoint - Epoch 43
This model is part of our reimplementation of the RoBERTa model,
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randomly initialized weights before the tra... | [
"# RoBERTa, Intermediate Checkpoint - Epoch 43\n\nThis model is part of our reimplementation of the RoBERTa model, \ntrained on Wikipedia and the Book Corpus only.\nWe train this model for almost 100K steps, corresponding to 83 epochs.\nWe provide the 84 checkpoints (including the randomly initialized weights befor... | [
"TAGS\n#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_43 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us \n",
"# RoBERTa, Intermediate Checkpoint - Epoch 43\n\nThis model is part of our... |
fill-mask | transformers |
# RoBERTa, Intermediate Checkpoint - Epoch 44
This model is part of our reimplementation of the [RoBERTa model](https://arxiv.org/abs/1907.11692),
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randoml... | {"language": "en", "license": "mit", "tags": ["roberta-base", "roberta-base-epoch_44"], "datasets": ["wikipedia", "bookcorpus"]} | yanaiela/roberta-base-epoch_44 | null | [
"transformers",
"pytorch",
"roberta",
"fill-mask",
"roberta-base",
"roberta-base-epoch_44",
"en",
"dataset:wikipedia",
"dataset:bookcorpus",
"arxiv:1907.11692",
"arxiv:2207.14251",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-28T16:24:01+00:00 | [
"1907.11692",
"2207.14251"
] | [
"en"
] | TAGS
#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_44 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us
|
# RoBERTa, Intermediate Checkpoint - Epoch 44
This model is part of our reimplementation of the RoBERTa model,
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randomly initialized weights before the tra... | [
"# RoBERTa, Intermediate Checkpoint - Epoch 44\n\nThis model is part of our reimplementation of the RoBERTa model, \ntrained on Wikipedia and the Book Corpus only.\nWe train this model for almost 100K steps, corresponding to 83 epochs.\nWe provide the 84 checkpoints (including the randomly initialized weights befor... | [
"TAGS\n#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_44 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us \n",
"# RoBERTa, Intermediate Checkpoint - Epoch 44\n\nThis model is part of our... |
fill-mask | transformers |
# RoBERTa, Intermediate Checkpoint - Epoch 45
This model is part of our reimplementation of the [RoBERTa model](https://arxiv.org/abs/1907.11692),
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randoml... | {"language": "en", "license": "mit", "tags": ["roberta-base", "roberta-base-epoch_45"], "datasets": ["wikipedia", "bookcorpus"]} | yanaiela/roberta-base-epoch_45 | null | [
"transformers",
"pytorch",
"roberta",
"fill-mask",
"roberta-base",
"roberta-base-epoch_45",
"en",
"dataset:wikipedia",
"dataset:bookcorpus",
"arxiv:1907.11692",
"arxiv:2207.14251",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-28T16:24:44+00:00 | [
"1907.11692",
"2207.14251"
] | [
"en"
] | TAGS
#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_45 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us
|
# RoBERTa, Intermediate Checkpoint - Epoch 45
This model is part of our reimplementation of the RoBERTa model,
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randomly initialized weights before the tra... | [
"# RoBERTa, Intermediate Checkpoint - Epoch 45\n\nThis model is part of our reimplementation of the RoBERTa model, \ntrained on Wikipedia and the Book Corpus only.\nWe train this model for almost 100K steps, corresponding to 83 epochs.\nWe provide the 84 checkpoints (including the randomly initialized weights befor... | [
"TAGS\n#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_45 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us \n",
"# RoBERTa, Intermediate Checkpoint - Epoch 45\n\nThis model is part of our... |
fill-mask | transformers |
# RoBERTa, Intermediate Checkpoint - Epoch 46
This model is part of our reimplementation of the [RoBERTa model](https://arxiv.org/abs/1907.11692),
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randoml... | {"language": "en", "license": "mit", "tags": ["roberta-base", "roberta-base-epoch_46"], "datasets": ["wikipedia", "bookcorpus"]} | yanaiela/roberta-base-epoch_46 | null | [
"transformers",
"pytorch",
"roberta",
"fill-mask",
"roberta-base",
"roberta-base-epoch_46",
"en",
"dataset:wikipedia",
"dataset:bookcorpus",
"arxiv:1907.11692",
"arxiv:2207.14251",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-28T16:25:28+00:00 | [
"1907.11692",
"2207.14251"
] | [
"en"
] | TAGS
#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_46 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us
|
# RoBERTa, Intermediate Checkpoint - Epoch 46
This model is part of our reimplementation of the RoBERTa model,
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randomly initialized weights before the tra... | [
"# RoBERTa, Intermediate Checkpoint - Epoch 46\n\nThis model is part of our reimplementation of the RoBERTa model, \ntrained on Wikipedia and the Book Corpus only.\nWe train this model for almost 100K steps, corresponding to 83 epochs.\nWe provide the 84 checkpoints (including the randomly initialized weights befor... | [
"TAGS\n#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_46 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us \n",
"# RoBERTa, Intermediate Checkpoint - Epoch 46\n\nThis model is part of our... |
fill-mask | transformers |
# RoBERTa, Intermediate Checkpoint - Epoch 47
This model is part of our reimplementation of the [RoBERTa model](https://arxiv.org/abs/1907.11692),
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randoml... | {"language": "en", "license": "mit", "tags": ["roberta-base", "roberta-base-epoch_47"], "datasets": ["wikipedia", "bookcorpus"]} | yanaiela/roberta-base-epoch_47 | null | [
"transformers",
"pytorch",
"roberta",
"fill-mask",
"roberta-base",
"roberta-base-epoch_47",
"en",
"dataset:wikipedia",
"dataset:bookcorpus",
"arxiv:1907.11692",
"arxiv:2207.14251",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-28T16:26:12+00:00 | [
"1907.11692",
"2207.14251"
] | [
"en"
] | TAGS
#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_47 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us
|
# RoBERTa, Intermediate Checkpoint - Epoch 47
This model is part of our reimplementation of the RoBERTa model,
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randomly initialized weights before the tra... | [
"# RoBERTa, Intermediate Checkpoint - Epoch 47\n\nThis model is part of our reimplementation of the RoBERTa model, \ntrained on Wikipedia and the Book Corpus only.\nWe train this model for almost 100K steps, corresponding to 83 epochs.\nWe provide the 84 checkpoints (including the randomly initialized weights befor... | [
"TAGS\n#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_47 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us \n",
"# RoBERTa, Intermediate Checkpoint - Epoch 47\n\nThis model is part of our... |
fill-mask | transformers |
# RoBERTa, Intermediate Checkpoint - Epoch 48
This model is part of our reimplementation of the [RoBERTa model](https://arxiv.org/abs/1907.11692),
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randoml... | {"language": "en", "license": "mit", "tags": ["roberta-base", "roberta-base-epoch_48"], "datasets": ["wikipedia", "bookcorpus"]} | yanaiela/roberta-base-epoch_48 | null | [
"transformers",
"pytorch",
"roberta",
"fill-mask",
"roberta-base",
"roberta-base-epoch_48",
"en",
"dataset:wikipedia",
"dataset:bookcorpus",
"arxiv:1907.11692",
"arxiv:2207.14251",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-28T16:26:55+00:00 | [
"1907.11692",
"2207.14251"
] | [
"en"
] | TAGS
#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_48 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us
|
# RoBERTa, Intermediate Checkpoint - Epoch 48
This model is part of our reimplementation of the RoBERTa model,
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randomly initialized weights before the tra... | [
"# RoBERTa, Intermediate Checkpoint - Epoch 48\n\nThis model is part of our reimplementation of the RoBERTa model, \ntrained on Wikipedia and the Book Corpus only.\nWe train this model for almost 100K steps, corresponding to 83 epochs.\nWe provide the 84 checkpoints (including the randomly initialized weights befor... | [
"TAGS\n#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_48 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us \n",
"# RoBERTa, Intermediate Checkpoint - Epoch 48\n\nThis model is part of our... |
text-classification | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# BERT_Mod_2
This model is a fine-tuned version of [distilbert-base-cased](https://huggingface.co/distilbert-base-cased) on the gl... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["glue"], "model-index": [{"name": "BERT_Mod_2", "results": []}]} | Go2Heart/BERT_Mod_2 | null | [
"transformers",
"pytorch",
"distilbert",
"text-classification",
"generated_from_trainer",
"dataset:glue",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-28T16:26:57+00:00 | [] | [] | TAGS
#transformers #pytorch #distilbert #text-classification #generated_from_trainer #dataset-glue #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
|
# BERT_Mod_2
This model is a fine-tuned version of distilbert-base-cased on the glue dataset.
It achieves the following results on the evaluation set:
- eval_loss: 0.5659
- eval_accuracy: 0.9037
- eval_runtime: 0.3838
- eval_samples_per_second: 2271.724
- eval_steps_per_second: 143.285
- epoch: 0.01
- step: 49
## ... | [
"# BERT_Mod_2\n\nThis model is a fine-tuned version of distilbert-base-cased on the glue dataset.\nIt achieves the following results on the evaluation set:\n- eval_loss: 0.5659\n- eval_accuracy: 0.9037\n- eval_runtime: 0.3838\n- eval_samples_per_second: 2271.724\n- eval_steps_per_second: 143.285\n- epoch: 0.01\n- s... | [
"TAGS\n#transformers #pytorch #distilbert #text-classification #generated_from_trainer #dataset-glue #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n",
"# BERT_Mod_2\n\nThis model is a fine-tuned version of distilbert-base-cased on the glue dataset.\nIt achieves the following results ... |
fill-mask | transformers |
# RoBERTa, Intermediate Checkpoint - Epoch 49
This model is part of our reimplementation of the [RoBERTa model](https://arxiv.org/abs/1907.11692),
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randoml... | {"language": "en", "license": "mit", "tags": ["roberta-base", "roberta-base-epoch_49"], "datasets": ["wikipedia", "bookcorpus"]} | yanaiela/roberta-base-epoch_49 | null | [
"transformers",
"pytorch",
"roberta",
"fill-mask",
"roberta-base",
"roberta-base-epoch_49",
"en",
"dataset:wikipedia",
"dataset:bookcorpus",
"arxiv:1907.11692",
"arxiv:2207.14251",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-28T16:27:40+00:00 | [
"1907.11692",
"2207.14251"
] | [
"en"
] | TAGS
#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_49 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us
|
# RoBERTa, Intermediate Checkpoint - Epoch 49
This model is part of our reimplementation of the RoBERTa model,
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randomly initialized weights before the tra... | [
"# RoBERTa, Intermediate Checkpoint - Epoch 49\n\nThis model is part of our reimplementation of the RoBERTa model, \ntrained on Wikipedia and the Book Corpus only.\nWe train this model for almost 100K steps, corresponding to 83 epochs.\nWe provide the 84 checkpoints (including the randomly initialized weights befor... | [
"TAGS\n#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_49 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us \n",
"# RoBERTa, Intermediate Checkpoint - Epoch 49\n\nThis model is part of our... |
fill-mask | transformers |
# RoBERTa, Intermediate Checkpoint - Epoch 50
This model is part of our reimplementation of the [RoBERTa model](https://arxiv.org/abs/1907.11692),
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randoml... | {"language": "en", "license": "mit", "tags": ["roberta-base", "roberta-base-epoch_50"], "datasets": ["wikipedia", "bookcorpus"]} | yanaiela/roberta-base-epoch_50 | null | [
"transformers",
"pytorch",
"roberta",
"fill-mask",
"roberta-base",
"roberta-base-epoch_50",
"en",
"dataset:wikipedia",
"dataset:bookcorpus",
"arxiv:1907.11692",
"arxiv:2207.14251",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-28T16:28:26+00:00 | [
"1907.11692",
"2207.14251"
] | [
"en"
] | TAGS
#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_50 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us
|
# RoBERTa, Intermediate Checkpoint - Epoch 50
This model is part of our reimplementation of the RoBERTa model,
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randomly initialized weights before the tra... | [
"# RoBERTa, Intermediate Checkpoint - Epoch 50\n\nThis model is part of our reimplementation of the RoBERTa model, \ntrained on Wikipedia and the Book Corpus only.\nWe train this model for almost 100K steps, corresponding to 83 epochs.\nWe provide the 84 checkpoints (including the randomly initialized weights befor... | [
"TAGS\n#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_50 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us \n",
"# RoBERTa, Intermediate Checkpoint - Epoch 50\n\nThis model is part of our... |
fill-mask | transformers |
# RoBERTa, Intermediate Checkpoint - Epoch 51
This model is part of our reimplementation of the [RoBERTa model](https://arxiv.org/abs/1907.11692),
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randoml... | {"language": "en", "license": "mit", "tags": ["roberta-base", "roberta-base-epoch_51"], "datasets": ["wikipedia", "bookcorpus"]} | yanaiela/roberta-base-epoch_51 | null | [
"transformers",
"pytorch",
"roberta",
"fill-mask",
"roberta-base",
"roberta-base-epoch_51",
"en",
"dataset:wikipedia",
"dataset:bookcorpus",
"arxiv:1907.11692",
"arxiv:2207.14251",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-28T16:29:17+00:00 | [
"1907.11692",
"2207.14251"
] | [
"en"
] | TAGS
#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_51 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us
|
# RoBERTa, Intermediate Checkpoint - Epoch 51
This model is part of our reimplementation of the RoBERTa model,
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randomly initialized weights before the tra... | [
"# RoBERTa, Intermediate Checkpoint - Epoch 51\n\nThis model is part of our reimplementation of the RoBERTa model, \ntrained on Wikipedia and the Book Corpus only.\nWe train this model for almost 100K steps, corresponding to 83 epochs.\nWe provide the 84 checkpoints (including the randomly initialized weights befor... | [
"TAGS\n#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_51 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us \n",
"# RoBERTa, Intermediate Checkpoint - Epoch 51\n\nThis model is part of our... |
fill-mask | transformers |
# RoBERTa, Intermediate Checkpoint - Epoch 52
This model is part of our reimplementation of the [RoBERTa model](https://arxiv.org/abs/1907.11692),
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randoml... | {"language": "en", "license": "mit", "tags": ["roberta-base", "roberta-base-epoch_52"], "datasets": ["wikipedia", "bookcorpus"]} | yanaiela/roberta-base-epoch_52 | null | [
"transformers",
"pytorch",
"roberta",
"fill-mask",
"roberta-base",
"roberta-base-epoch_52",
"en",
"dataset:wikipedia",
"dataset:bookcorpus",
"arxiv:1907.11692",
"arxiv:2207.14251",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-28T16:30:02+00:00 | [
"1907.11692",
"2207.14251"
] | [
"en"
] | TAGS
#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_52 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us
|
# RoBERTa, Intermediate Checkpoint - Epoch 52
This model is part of our reimplementation of the RoBERTa model,
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randomly initialized weights before the tra... | [
"# RoBERTa, Intermediate Checkpoint - Epoch 52\n\nThis model is part of our reimplementation of the RoBERTa model, \ntrained on Wikipedia and the Book Corpus only.\nWe train this model for almost 100K steps, corresponding to 83 epochs.\nWe provide the 84 checkpoints (including the randomly initialized weights befor... | [
"TAGS\n#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_52 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us \n",
"# RoBERTa, Intermediate Checkpoint - Epoch 52\n\nThis model is part of our... |
fill-mask | transformers |
# RoBERTa, Intermediate Checkpoint - Epoch 53
This model is part of our reimplementation of the [RoBERTa model](https://arxiv.org/abs/1907.11692),
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randoml... | {"language": "en", "license": "mit", "tags": ["roberta-base", "roberta-base-epoch_53"], "datasets": ["wikipedia", "bookcorpus"]} | yanaiela/roberta-base-epoch_53 | null | [
"transformers",
"pytorch",
"roberta",
"fill-mask",
"roberta-base",
"roberta-base-epoch_53",
"en",
"dataset:wikipedia",
"dataset:bookcorpus",
"arxiv:1907.11692",
"arxiv:2207.14251",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-28T16:30:47+00:00 | [
"1907.11692",
"2207.14251"
] | [
"en"
] | TAGS
#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_53 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us
|
# RoBERTa, Intermediate Checkpoint - Epoch 53
This model is part of our reimplementation of the RoBERTa model,
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randomly initialized weights before the tra... | [
"# RoBERTa, Intermediate Checkpoint - Epoch 53\n\nThis model is part of our reimplementation of the RoBERTa model, \ntrained on Wikipedia and the Book Corpus only.\nWe train this model for almost 100K steps, corresponding to 83 epochs.\nWe provide the 84 checkpoints (including the randomly initialized weights befor... | [
"TAGS\n#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_53 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us \n",
"# RoBERTa, Intermediate Checkpoint - Epoch 53\n\nThis model is part of our... |
fill-mask | transformers |
# RoBERTa, Intermediate Checkpoint - Epoch 54
This model is part of our reimplementation of the [RoBERTa model](https://arxiv.org/abs/1907.11692),
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randoml... | {"language": "en", "license": "mit", "tags": ["roberta-base", "roberta-base-epoch_54"], "datasets": ["wikipedia", "bookcorpus"]} | yanaiela/roberta-base-epoch_54 | null | [
"transformers",
"pytorch",
"roberta",
"fill-mask",
"roberta-base",
"roberta-base-epoch_54",
"en",
"dataset:wikipedia",
"dataset:bookcorpus",
"arxiv:1907.11692",
"arxiv:2207.14251",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-28T16:31:39+00:00 | [
"1907.11692",
"2207.14251"
] | [
"en"
] | TAGS
#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_54 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us
|
# RoBERTa, Intermediate Checkpoint - Epoch 54
This model is part of our reimplementation of the RoBERTa model,
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randomly initialized weights before the tra... | [
"# RoBERTa, Intermediate Checkpoint - Epoch 54\n\nThis model is part of our reimplementation of the RoBERTa model, \ntrained on Wikipedia and the Book Corpus only.\nWe train this model for almost 100K steps, corresponding to 83 epochs.\nWe provide the 84 checkpoints (including the randomly initialized weights befor... | [
"TAGS\n#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_54 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us \n",
"# RoBERTa, Intermediate Checkpoint - Epoch 54\n\nThis model is part of our... |
fill-mask | transformers |
# RoBERTa, Intermediate Checkpoint - Epoch 55
This model is part of our reimplementation of the [RoBERTa model](https://arxiv.org/abs/1907.11692),
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randoml... | {"language": "en", "license": "mit", "tags": ["roberta-base", "roberta-base-epoch_55"], "datasets": ["wikipedia", "bookcorpus"]} | yanaiela/roberta-base-epoch_55 | null | [
"transformers",
"pytorch",
"roberta",
"fill-mask",
"roberta-base",
"roberta-base-epoch_55",
"en",
"dataset:wikipedia",
"dataset:bookcorpus",
"arxiv:1907.11692",
"arxiv:2207.14251",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-28T16:32:24+00:00 | [
"1907.11692",
"2207.14251"
] | [
"en"
] | TAGS
#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_55 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us
|
# RoBERTa, Intermediate Checkpoint - Epoch 55
This model is part of our reimplementation of the RoBERTa model,
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randomly initialized weights before the tra... | [
"# RoBERTa, Intermediate Checkpoint - Epoch 55\n\nThis model is part of our reimplementation of the RoBERTa model, \ntrained on Wikipedia and the Book Corpus only.\nWe train this model for almost 100K steps, corresponding to 83 epochs.\nWe provide the 84 checkpoints (including the randomly initialized weights befor... | [
"TAGS\n#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_55 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us \n",
"# RoBERTa, Intermediate Checkpoint - Epoch 55\n\nThis model is part of our... |
fill-mask | transformers |
# RoBERTa, Intermediate Checkpoint - Epoch 56
This model is part of our reimplementation of the [RoBERTa model](https://arxiv.org/abs/1907.11692),
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randoml... | {"language": "en", "license": "mit", "tags": ["roberta-base", "roberta-base-epoch_56"], "datasets": ["wikipedia", "bookcorpus"]} | yanaiela/roberta-base-epoch_56 | null | [
"transformers",
"pytorch",
"roberta",
"fill-mask",
"roberta-base",
"roberta-base-epoch_56",
"en",
"dataset:wikipedia",
"dataset:bookcorpus",
"arxiv:1907.11692",
"arxiv:2207.14251",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-28T16:33:29+00:00 | [
"1907.11692",
"2207.14251"
] | [
"en"
] | TAGS
#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_56 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us
|
# RoBERTa, Intermediate Checkpoint - Epoch 56
This model is part of our reimplementation of the RoBERTa model,
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randomly initialized weights before the tra... | [
"# RoBERTa, Intermediate Checkpoint - Epoch 56\n\nThis model is part of our reimplementation of the RoBERTa model, \ntrained on Wikipedia and the Book Corpus only.\nWe train this model for almost 100K steps, corresponding to 83 epochs.\nWe provide the 84 checkpoints (including the randomly initialized weights befor... | [
"TAGS\n#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_56 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us \n",
"# RoBERTa, Intermediate Checkpoint - Epoch 56\n\nThis model is part of our... |
fill-mask | transformers |
# RoBERTa, Intermediate Checkpoint - Epoch 57
This model is part of our reimplementation of the [RoBERTa model](https://arxiv.org/abs/1907.11692),
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randoml... | {"language": "en", "license": "mit", "tags": ["roberta-base", "roberta-base-epoch_57"], "datasets": ["wikipedia", "bookcorpus"]} | yanaiela/roberta-base-epoch_57 | null | [
"transformers",
"pytorch",
"roberta",
"fill-mask",
"roberta-base",
"roberta-base-epoch_57",
"en",
"dataset:wikipedia",
"dataset:bookcorpus",
"arxiv:1907.11692",
"arxiv:2207.14251",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-28T16:34:22+00:00 | [
"1907.11692",
"2207.14251"
] | [
"en"
] | TAGS
#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_57 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us
|
# RoBERTa, Intermediate Checkpoint - Epoch 57
This model is part of our reimplementation of the RoBERTa model,
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randomly initialized weights before the tra... | [
"# RoBERTa, Intermediate Checkpoint - Epoch 57\n\nThis model is part of our reimplementation of the RoBERTa model, \ntrained on Wikipedia and the Book Corpus only.\nWe train this model for almost 100K steps, corresponding to 83 epochs.\nWe provide the 84 checkpoints (including the randomly initialized weights befor... | [
"TAGS\n#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_57 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us \n",
"# RoBERTa, Intermediate Checkpoint - Epoch 57\n\nThis model is part of our... |
fill-mask | transformers |
# RoBERTa, Intermediate Checkpoint - Epoch 58
This model is part of our reimplementation of the [RoBERTa model](https://arxiv.org/abs/1907.11692),
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randoml... | {"language": "en", "license": "mit", "tags": ["roberta-base", "roberta-base-epoch_58"], "datasets": ["wikipedia", "bookcorpus"]} | yanaiela/roberta-base-epoch_58 | null | [
"transformers",
"pytorch",
"roberta",
"fill-mask",
"roberta-base",
"roberta-base-epoch_58",
"en",
"dataset:wikipedia",
"dataset:bookcorpus",
"arxiv:1907.11692",
"arxiv:2207.14251",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-28T16:35:06+00:00 | [
"1907.11692",
"2207.14251"
] | [
"en"
] | TAGS
#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_58 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us
|
# RoBERTa, Intermediate Checkpoint - Epoch 58
This model is part of our reimplementation of the RoBERTa model,
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randomly initialized weights before the tra... | [
"# RoBERTa, Intermediate Checkpoint - Epoch 58\n\nThis model is part of our reimplementation of the RoBERTa model, \ntrained on Wikipedia and the Book Corpus only.\nWe train this model for almost 100K steps, corresponding to 83 epochs.\nWe provide the 84 checkpoints (including the randomly initialized weights befor... | [
"TAGS\n#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_58 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us \n",
"# RoBERTa, Intermediate Checkpoint - Epoch 58\n\nThis model is part of our... |
fill-mask | transformers |
# RoBERTa, Intermediate Checkpoint - Epoch 59
This model is part of our reimplementation of the [RoBERTa model](https://arxiv.org/abs/1907.11692),
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randoml... | {"language": "en", "license": "mit", "tags": ["roberta-base", "roberta-base-epoch_59"], "datasets": ["wikipedia", "bookcorpus"]} | yanaiela/roberta-base-epoch_59 | null | [
"transformers",
"pytorch",
"roberta",
"fill-mask",
"roberta-base",
"roberta-base-epoch_59",
"en",
"dataset:wikipedia",
"dataset:bookcorpus",
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"arxiv:2207.14251",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-28T16:35:53+00:00 | [
"1907.11692",
"2207.14251"
] | [
"en"
] | TAGS
#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_59 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us
|
# RoBERTa, Intermediate Checkpoint - Epoch 59
This model is part of our reimplementation of the RoBERTa model,
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randomly initialized weights before the tra... | [
"# RoBERTa, Intermediate Checkpoint - Epoch 59\n\nThis model is part of our reimplementation of the RoBERTa model, \ntrained on Wikipedia and the Book Corpus only.\nWe train this model for almost 100K steps, corresponding to 83 epochs.\nWe provide the 84 checkpoints (including the randomly initialized weights befor... | [
"TAGS\n#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_59 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us \n",
"# RoBERTa, Intermediate Checkpoint - Epoch 59\n\nThis model is part of our... |
fill-mask | transformers |
# RoBERTa, Intermediate Checkpoint - Epoch 60
This model is part of our reimplementation of the [RoBERTa model](https://arxiv.org/abs/1907.11692),
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randoml... | {"language": "en", "license": "mit", "tags": ["roberta-base", "roberta-base-epoch_60"], "datasets": ["wikipedia", "bookcorpus"]} | yanaiela/roberta-base-epoch_60 | null | [
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"arxiv:1907.11692",
"arxiv:2207.14251",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-28T16:36:36+00:00 | [
"1907.11692",
"2207.14251"
] | [
"en"
] | TAGS
#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_60 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us
|
# RoBERTa, Intermediate Checkpoint - Epoch 60
This model is part of our reimplementation of the RoBERTa model,
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randomly initialized weights before the tra... | [
"# RoBERTa, Intermediate Checkpoint - Epoch 60\n\nThis model is part of our reimplementation of the RoBERTa model, \ntrained on Wikipedia and the Book Corpus only.\nWe train this model for almost 100K steps, corresponding to 83 epochs.\nWe provide the 84 checkpoints (including the randomly initialized weights befor... | [
"TAGS\n#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_60 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us \n",
"# RoBERTa, Intermediate Checkpoint - Epoch 60\n\nThis model is part of our... |
fill-mask | transformers |
# RoBERTa, Intermediate Checkpoint - Epoch 61
This model is part of our reimplementation of the [RoBERTa model](https://arxiv.org/abs/1907.11692),
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randoml... | {"language": "en", "license": "mit", "tags": ["roberta-base", "roberta-base-epoch_61"], "datasets": ["wikipedia", "bookcorpus"]} | yanaiela/roberta-base-epoch_61 | null | [
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"en",
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"arxiv:1907.11692",
"arxiv:2207.14251",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-28T16:39:32+00:00 | [
"1907.11692",
"2207.14251"
] | [
"en"
] | TAGS
#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_61 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us
|
# RoBERTa, Intermediate Checkpoint - Epoch 61
This model is part of our reimplementation of the RoBERTa model,
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randomly initialized weights before the tra... | [
"# RoBERTa, Intermediate Checkpoint - Epoch 61\n\nThis model is part of our reimplementation of the RoBERTa model, \ntrained on Wikipedia and the Book Corpus only.\nWe train this model for almost 100K steps, corresponding to 83 epochs.\nWe provide the 84 checkpoints (including the randomly initialized weights befor... | [
"TAGS\n#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_61 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us \n",
"# RoBERTa, Intermediate Checkpoint - Epoch 61\n\nThis model is part of our... |
fill-mask | transformers |
# RoBERTa, Intermediate Checkpoint - Epoch 62
This model is part of our reimplementation of the [RoBERTa model](https://arxiv.org/abs/1907.11692),
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randoml... | {"language": "en", "license": "mit", "tags": ["roberta-base", "roberta-base-epoch_62"], "datasets": ["wikipedia", "bookcorpus"]} | yanaiela/roberta-base-epoch_62 | null | [
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"roberta-base-epoch_62",
"en",
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"dataset:bookcorpus",
"arxiv:1907.11692",
"arxiv:2207.14251",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-28T16:41:02+00:00 | [
"1907.11692",
"2207.14251"
] | [
"en"
] | TAGS
#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_62 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us
|
# RoBERTa, Intermediate Checkpoint - Epoch 62
This model is part of our reimplementation of the RoBERTa model,
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randomly initialized weights before the tra... | [
"# RoBERTa, Intermediate Checkpoint - Epoch 62\n\nThis model is part of our reimplementation of the RoBERTa model, \ntrained on Wikipedia and the Book Corpus only.\nWe train this model for almost 100K steps, corresponding to 83 epochs.\nWe provide the 84 checkpoints (including the randomly initialized weights befor... | [
"TAGS\n#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_62 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us \n",
"# RoBERTa, Intermediate Checkpoint - Epoch 62\n\nThis model is part of our... |
fill-mask | transformers |
# RoBERTa, Intermediate Checkpoint - Epoch 63
This model is part of our reimplementation of the [RoBERTa model](https://arxiv.org/abs/1907.11692),
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randoml... | {"language": "en", "license": "mit", "tags": ["roberta-base", "roberta-base-epoch_63"], "datasets": ["wikipedia", "bookcorpus"]} | yanaiela/roberta-base-epoch_63 | null | [
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"en",
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"dataset:bookcorpus",
"arxiv:1907.11692",
"arxiv:2207.14251",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-28T16:42:21+00:00 | [
"1907.11692",
"2207.14251"
] | [
"en"
] | TAGS
#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_63 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us
|
# RoBERTa, Intermediate Checkpoint - Epoch 63
This model is part of our reimplementation of the RoBERTa model,
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randomly initialized weights before the tra... | [
"# RoBERTa, Intermediate Checkpoint - Epoch 63\n\nThis model is part of our reimplementation of the RoBERTa model, \ntrained on Wikipedia and the Book Corpus only.\nWe train this model for almost 100K steps, corresponding to 83 epochs.\nWe provide the 84 checkpoints (including the randomly initialized weights befor... | [
"TAGS\n#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_63 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us \n",
"# RoBERTa, Intermediate Checkpoint - Epoch 63\n\nThis model is part of our... |
fill-mask | transformers |
# RoBERTa, Intermediate Checkpoint - Epoch 64
This model is part of our reimplementation of the [RoBERTa model](https://arxiv.org/abs/1907.11692),
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randoml... | {"language": "en", "license": "mit", "tags": ["roberta-base", "roberta-base-epoch_64"], "datasets": ["wikipedia", "bookcorpus"]} | yanaiela/roberta-base-epoch_64 | null | [
"transformers",
"pytorch",
"roberta",
"fill-mask",
"roberta-base",
"roberta-base-epoch_64",
"en",
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"dataset:bookcorpus",
"arxiv:1907.11692",
"arxiv:2207.14251",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-28T16:43:33+00:00 | [
"1907.11692",
"2207.14251"
] | [
"en"
] | TAGS
#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_64 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us
|
# RoBERTa, Intermediate Checkpoint - Epoch 64
This model is part of our reimplementation of the RoBERTa model,
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randomly initialized weights before the tra... | [
"# RoBERTa, Intermediate Checkpoint - Epoch 64\n\nThis model is part of our reimplementation of the RoBERTa model, \ntrained on Wikipedia and the Book Corpus only.\nWe train this model for almost 100K steps, corresponding to 83 epochs.\nWe provide the 84 checkpoints (including the randomly initialized weights befor... | [
"TAGS\n#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_64 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us \n",
"# RoBERTa, Intermediate Checkpoint - Epoch 64\n\nThis model is part of our... |
fill-mask | transformers |
# RoBERTa, Intermediate Checkpoint - Epoch 65
This model is part of our reimplementation of the [RoBERTa model](https://arxiv.org/abs/1907.11692),
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randoml... | {"language": "en", "license": "mit", "tags": ["roberta-base", "roberta-base-epoch_65"], "datasets": ["wikipedia", "bookcorpus"]} | yanaiela/roberta-base-epoch_65 | null | [
"transformers",
"pytorch",
"roberta",
"fill-mask",
"roberta-base",
"roberta-base-epoch_65",
"en",
"dataset:wikipedia",
"dataset:bookcorpus",
"arxiv:1907.11692",
"arxiv:2207.14251",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-28T16:45:42+00:00 | [
"1907.11692",
"2207.14251"
] | [
"en"
] | TAGS
#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_65 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us
|
# RoBERTa, Intermediate Checkpoint - Epoch 65
This model is part of our reimplementation of the RoBERTa model,
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randomly initialized weights before the tra... | [
"# RoBERTa, Intermediate Checkpoint - Epoch 65\n\nThis model is part of our reimplementation of the RoBERTa model, \ntrained on Wikipedia and the Book Corpus only.\nWe train this model for almost 100K steps, corresponding to 83 epochs.\nWe provide the 84 checkpoints (including the randomly initialized weights befor... | [
"TAGS\n#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_65 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us \n",
"# RoBERTa, Intermediate Checkpoint - Epoch 65\n\nThis model is part of our... |
fill-mask | transformers |
# RoBERTa, Intermediate Checkpoint - Epoch 66
This model is part of our reimplementation of the [RoBERTa model](https://arxiv.org/abs/1907.11692),
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randoml... | {"language": "en", "license": "mit", "tags": ["roberta-base", "roberta-base-epoch_66"], "datasets": ["wikipedia", "bookcorpus"]} | yanaiela/roberta-base-epoch_66 | null | [
"transformers",
"pytorch",
"roberta",
"fill-mask",
"roberta-base",
"roberta-base-epoch_66",
"en",
"dataset:wikipedia",
"dataset:bookcorpus",
"arxiv:1907.11692",
"arxiv:2207.14251",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-28T16:46:45+00:00 | [
"1907.11692",
"2207.14251"
] | [
"en"
] | TAGS
#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_66 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us
|
# RoBERTa, Intermediate Checkpoint - Epoch 66
This model is part of our reimplementation of the RoBERTa model,
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randomly initialized weights before the tra... | [
"# RoBERTa, Intermediate Checkpoint - Epoch 66\n\nThis model is part of our reimplementation of the RoBERTa model, \ntrained on Wikipedia and the Book Corpus only.\nWe train this model for almost 100K steps, corresponding to 83 epochs.\nWe provide the 84 checkpoints (including the randomly initialized weights befor... | [
"TAGS\n#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_66 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us \n",
"# RoBERTa, Intermediate Checkpoint - Epoch 66\n\nThis model is part of our... |
fill-mask | transformers |
# RoBERTa, Intermediate Checkpoint - Epoch 67
This model is part of our reimplementation of the [RoBERTa model](https://arxiv.org/abs/1907.11692),
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randoml... | {"language": "en", "license": "mit", "tags": ["roberta-base", "roberta-base-epoch_67"], "datasets": ["wikipedia", "bookcorpus"]} | yanaiela/roberta-base-epoch_67 | null | [
"transformers",
"pytorch",
"roberta",
"fill-mask",
"roberta-base",
"roberta-base-epoch_67",
"en",
"dataset:wikipedia",
"dataset:bookcorpus",
"arxiv:1907.11692",
"arxiv:2207.14251",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-28T16:48:39+00:00 | [
"1907.11692",
"2207.14251"
] | [
"en"
] | TAGS
#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_67 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us
|
# RoBERTa, Intermediate Checkpoint - Epoch 67
This model is part of our reimplementation of the RoBERTa model,
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randomly initialized weights before the tra... | [
"# RoBERTa, Intermediate Checkpoint - Epoch 67\n\nThis model is part of our reimplementation of the RoBERTa model, \ntrained on Wikipedia and the Book Corpus only.\nWe train this model for almost 100K steps, corresponding to 83 epochs.\nWe provide the 84 checkpoints (including the randomly initialized weights befor... | [
"TAGS\n#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_67 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us \n",
"# RoBERTa, Intermediate Checkpoint - Epoch 67\n\nThis model is part of our... |
fill-mask | transformers |
# RoBERTa, Intermediate Checkpoint - Epoch 68
This model is part of our reimplementation of the [RoBERTa model](https://arxiv.org/abs/1907.11692),
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randoml... | {"language": "en", "license": "mit", "tags": ["roberta-base", "roberta-base-epoch_68"], "datasets": ["wikipedia", "bookcorpus"]} | yanaiela/roberta-base-epoch_68 | null | [
"transformers",
"pytorch",
"roberta",
"fill-mask",
"roberta-base",
"roberta-base-epoch_68",
"en",
"dataset:wikipedia",
"dataset:bookcorpus",
"arxiv:1907.11692",
"arxiv:2207.14251",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-28T16:50:00+00:00 | [
"1907.11692",
"2207.14251"
] | [
"en"
] | TAGS
#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_68 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us
|
# RoBERTa, Intermediate Checkpoint - Epoch 68
This model is part of our reimplementation of the RoBERTa model,
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randomly initialized weights before the tra... | [
"# RoBERTa, Intermediate Checkpoint - Epoch 68\n\nThis model is part of our reimplementation of the RoBERTa model, \ntrained on Wikipedia and the Book Corpus only.\nWe train this model for almost 100K steps, corresponding to 83 epochs.\nWe provide the 84 checkpoints (including the randomly initialized weights befor... | [
"TAGS\n#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_68 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us \n",
"# RoBERTa, Intermediate Checkpoint - Epoch 68\n\nThis model is part of our... |
fill-mask | transformers |
# RoBERTa, Intermediate Checkpoint - Epoch 69
This model is part of our reimplementation of the [RoBERTa model](https://arxiv.org/abs/1907.11692),
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randoml... | {"language": "en", "license": "mit", "tags": ["roberta-base", "roberta-base-epoch_69"], "datasets": ["wikipedia", "bookcorpus"]} | yanaiela/roberta-base-epoch_69 | null | [
"transformers",
"pytorch",
"roberta",
"fill-mask",
"roberta-base",
"roberta-base-epoch_69",
"en",
"dataset:wikipedia",
"dataset:bookcorpus",
"arxiv:1907.11692",
"arxiv:2207.14251",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-28T16:50:57+00:00 | [
"1907.11692",
"2207.14251"
] | [
"en"
] | TAGS
#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_69 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us
|
# RoBERTa, Intermediate Checkpoint - Epoch 69
This model is part of our reimplementation of the RoBERTa model,
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randomly initialized weights before the tra... | [
"# RoBERTa, Intermediate Checkpoint - Epoch 69\n\nThis model is part of our reimplementation of the RoBERTa model, \ntrained on Wikipedia and the Book Corpus only.\nWe train this model for almost 100K steps, corresponding to 83 epochs.\nWe provide the 84 checkpoints (including the randomly initialized weights befor... | [
"TAGS\n#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_69 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us \n",
"# RoBERTa, Intermediate Checkpoint - Epoch 69\n\nThis model is part of our... |
fill-mask | transformers |
# RoBERTa, Intermediate Checkpoint - Epoch 70
This model is part of our reimplementation of the [RoBERTa model](https://arxiv.org/abs/1907.11692),
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randoml... | {"language": "en", "license": "mit", "tags": ["roberta-base", "roberta-base-epoch_70"], "datasets": ["wikipedia", "bookcorpus"]} | yanaiela/roberta-base-epoch_70 | null | [
"transformers",
"pytorch",
"roberta",
"fill-mask",
"roberta-base",
"roberta-base-epoch_70",
"en",
"dataset:wikipedia",
"dataset:bookcorpus",
"arxiv:1907.11692",
"arxiv:2207.14251",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-28T16:52:21+00:00 | [
"1907.11692",
"2207.14251"
] | [
"en"
] | TAGS
#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_70 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us
|
# RoBERTa, Intermediate Checkpoint - Epoch 70
This model is part of our reimplementation of the RoBERTa model,
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randomly initialized weights before the tra... | [
"# RoBERTa, Intermediate Checkpoint - Epoch 70\n\nThis model is part of our reimplementation of the RoBERTa model, \ntrained on Wikipedia and the Book Corpus only.\nWe train this model for almost 100K steps, corresponding to 83 epochs.\nWe provide the 84 checkpoints (including the randomly initialized weights befor... | [
"TAGS\n#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_70 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us \n",
"# RoBERTa, Intermediate Checkpoint - Epoch 70\n\nThis model is part of our... |
fill-mask | transformers |
# RoBERTa, Intermediate Checkpoint - Epoch 71
This model is part of our reimplementation of the [RoBERTa model](https://arxiv.org/abs/1907.11692),
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randoml... | {"language": "en", "license": "mit", "tags": ["roberta-base", "roberta-base-epoch_71"], "datasets": ["wikipedia", "bookcorpus"]} | yanaiela/roberta-base-epoch_71 | null | [
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"arxiv:2207.14251",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-28T16:53:19+00:00 | [
"1907.11692",
"2207.14251"
] | [
"en"
] | TAGS
#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_71 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us
|
# RoBERTa, Intermediate Checkpoint - Epoch 71
This model is part of our reimplementation of the RoBERTa model,
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randomly initialized weights before the tra... | [
"# RoBERTa, Intermediate Checkpoint - Epoch 71\n\nThis model is part of our reimplementation of the RoBERTa model, \ntrained on Wikipedia and the Book Corpus only.\nWe train this model for almost 100K steps, corresponding to 83 epochs.\nWe provide the 84 checkpoints (including the randomly initialized weights befor... | [
"TAGS\n#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_71 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us \n",
"# RoBERTa, Intermediate Checkpoint - Epoch 71\n\nThis model is part of our... |
fill-mask | transformers |
# RoBERTa, Intermediate Checkpoint - Epoch 72
This model is part of our reimplementation of the [RoBERTa model](https://arxiv.org/abs/1907.11692),
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randoml... | {"language": "en", "license": "mit", "tags": ["roberta-base", "roberta-base-epoch_72"], "datasets": ["wikipedia", "bookcorpus"]} | yanaiela/roberta-base-epoch_72 | null | [
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"fill-mask",
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"en",
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"arxiv:1907.11692",
"arxiv:2207.14251",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-28T16:54:57+00:00 | [
"1907.11692",
"2207.14251"
] | [
"en"
] | TAGS
#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_72 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us
|
# RoBERTa, Intermediate Checkpoint - Epoch 72
This model is part of our reimplementation of the RoBERTa model,
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randomly initialized weights before the tra... | [
"# RoBERTa, Intermediate Checkpoint - Epoch 72\n\nThis model is part of our reimplementation of the RoBERTa model, \ntrained on Wikipedia and the Book Corpus only.\nWe train this model for almost 100K steps, corresponding to 83 epochs.\nWe provide the 84 checkpoints (including the randomly initialized weights befor... | [
"TAGS\n#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_72 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us \n",
"# RoBERTa, Intermediate Checkpoint - Epoch 72\n\nThis model is part of our... |
fill-mask | transformers |
# RoBERTa, Intermediate Checkpoint - Epoch 73
This model is part of our reimplementation of the [RoBERTa model](https://arxiv.org/abs/1907.11692),
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randoml... | {"language": "en", "license": "mit", "tags": ["roberta-base", "roberta-base-epoch_73"], "datasets": ["wikipedia", "bookcorpus"]} | yanaiela/roberta-base-epoch_73 | null | [
"transformers",
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"fill-mask",
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"en",
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"arxiv:1907.11692",
"arxiv:2207.14251",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-28T16:55:51+00:00 | [
"1907.11692",
"2207.14251"
] | [
"en"
] | TAGS
#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_73 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us
|
# RoBERTa, Intermediate Checkpoint - Epoch 73
This model is part of our reimplementation of the RoBERTa model,
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randomly initialized weights before the tra... | [
"# RoBERTa, Intermediate Checkpoint - Epoch 73\n\nThis model is part of our reimplementation of the RoBERTa model, \ntrained on Wikipedia and the Book Corpus only.\nWe train this model for almost 100K steps, corresponding to 83 epochs.\nWe provide the 84 checkpoints (including the randomly initialized weights befor... | [
"TAGS\n#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_73 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us \n",
"# RoBERTa, Intermediate Checkpoint - Epoch 73\n\nThis model is part of our... |
fill-mask | transformers |
# RoBERTa, Intermediate Checkpoint - Epoch 74
This model is part of our reimplementation of the [RoBERTa model](https://arxiv.org/abs/1907.11692),
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randoml... | {"language": "en", "license": "mit", "tags": ["roberta-base", "roberta-base-epoch_74"], "datasets": ["wikipedia", "bookcorpus"]} | yanaiela/roberta-base-epoch_74 | null | [
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"roberta",
"fill-mask",
"roberta-base",
"roberta-base-epoch_74",
"en",
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"dataset:bookcorpus",
"arxiv:1907.11692",
"arxiv:2207.14251",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-28T16:56:39+00:00 | [
"1907.11692",
"2207.14251"
] | [
"en"
] | TAGS
#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_74 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us
|
# RoBERTa, Intermediate Checkpoint - Epoch 74
This model is part of our reimplementation of the RoBERTa model,
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randomly initialized weights before the tra... | [
"# RoBERTa, Intermediate Checkpoint - Epoch 74\n\nThis model is part of our reimplementation of the RoBERTa model, \ntrained on Wikipedia and the Book Corpus only.\nWe train this model for almost 100K steps, corresponding to 83 epochs.\nWe provide the 84 checkpoints (including the randomly initialized weights befor... | [
"TAGS\n#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_74 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us \n",
"# RoBERTa, Intermediate Checkpoint - Epoch 74\n\nThis model is part of our... |
fill-mask | transformers |
# RoBERTa, Intermediate Checkpoint - Epoch 75
This model is part of our reimplementation of the [RoBERTa model](https://arxiv.org/abs/1907.11692),
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randoml... | {"language": "en", "license": "mit", "tags": ["roberta-base", "roberta-base-epoch_75"], "datasets": ["wikipedia", "bookcorpus"]} | yanaiela/roberta-base-epoch_75 | null | [
"transformers",
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"roberta",
"fill-mask",
"roberta-base",
"roberta-base-epoch_75",
"en",
"dataset:wikipedia",
"dataset:bookcorpus",
"arxiv:1907.11692",
"arxiv:2207.14251",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-28T16:57:46+00:00 | [
"1907.11692",
"2207.14251"
] | [
"en"
] | TAGS
#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_75 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us
|
# RoBERTa, Intermediate Checkpoint - Epoch 75
This model is part of our reimplementation of the RoBERTa model,
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randomly initialized weights before the tra... | [
"# RoBERTa, Intermediate Checkpoint - Epoch 75\n\nThis model is part of our reimplementation of the RoBERTa model, \ntrained on Wikipedia and the Book Corpus only.\nWe train this model for almost 100K steps, corresponding to 83 epochs.\nWe provide the 84 checkpoints (including the randomly initialized weights befor... | [
"TAGS\n#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_75 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us \n",
"# RoBERTa, Intermediate Checkpoint - Epoch 75\n\nThis model is part of our... |
fill-mask | transformers |
# RoBERTa, Intermediate Checkpoint - Epoch 76
This model is part of our reimplementation of the [RoBERTa model](https://arxiv.org/abs/1907.11692),
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randoml... | {"language": "en", "license": "mit", "tags": ["roberta-base", "roberta-base-epoch_76"], "datasets": ["wikipedia", "bookcorpus"]} | yanaiela/roberta-base-epoch_76 | null | [
"transformers",
"pytorch",
"roberta",
"fill-mask",
"roberta-base",
"roberta-base-epoch_76",
"en",
"dataset:wikipedia",
"dataset:bookcorpus",
"arxiv:1907.11692",
"arxiv:2207.14251",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-28T16:58:41+00:00 | [
"1907.11692",
"2207.14251"
] | [
"en"
] | TAGS
#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_76 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us
|
# RoBERTa, Intermediate Checkpoint - Epoch 76
This model is part of our reimplementation of the RoBERTa model,
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randomly initialized weights before the tra... | [
"# RoBERTa, Intermediate Checkpoint - Epoch 76\n\nThis model is part of our reimplementation of the RoBERTa model, \ntrained on Wikipedia and the Book Corpus only.\nWe train this model for almost 100K steps, corresponding to 83 epochs.\nWe provide the 84 checkpoints (including the randomly initialized weights befor... | [
"TAGS\n#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_76 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us \n",
"# RoBERTa, Intermediate Checkpoint - Epoch 76\n\nThis model is part of our... |
fill-mask | transformers |
# RoBERTa, Intermediate Checkpoint - Epoch 77
This model is part of our reimplementation of the [RoBERTa model](https://arxiv.org/abs/1907.11692),
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randoml... | {"language": "en", "license": "mit", "tags": ["roberta-base", "roberta-base-epoch_77"], "datasets": ["wikipedia", "bookcorpus"]} | yanaiela/roberta-base-epoch_77 | null | [
"transformers",
"pytorch",
"roberta",
"fill-mask",
"roberta-base",
"roberta-base-epoch_77",
"en",
"dataset:wikipedia",
"dataset:bookcorpus",
"arxiv:1907.11692",
"arxiv:2207.14251",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-28T16:59:57+00:00 | [
"1907.11692",
"2207.14251"
] | [
"en"
] | TAGS
#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_77 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us
|
# RoBERTa, Intermediate Checkpoint - Epoch 77
This model is part of our reimplementation of the RoBERTa model,
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randomly initialized weights before the tra... | [
"# RoBERTa, Intermediate Checkpoint - Epoch 77\n\nThis model is part of our reimplementation of the RoBERTa model, \ntrained on Wikipedia and the Book Corpus only.\nWe train this model for almost 100K steps, corresponding to 83 epochs.\nWe provide the 84 checkpoints (including the randomly initialized weights befor... | [
"TAGS\n#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_77 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us \n",
"# RoBERTa, Intermediate Checkpoint - Epoch 77\n\nThis model is part of our... |
fill-mask | transformers |
# RoBERTa, Intermediate Checkpoint - Epoch 78
This model is part of our reimplementation of the [RoBERTa model](https://arxiv.org/abs/1907.11692),
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randoml... | {"language": "en", "license": "mit", "tags": ["roberta-base", "roberta-base-epoch_78"], "datasets": ["wikipedia", "bookcorpus"]} | yanaiela/roberta-base-epoch_78 | null | [
"transformers",
"pytorch",
"roberta",
"fill-mask",
"roberta-base",
"roberta-base-epoch_78",
"en",
"dataset:wikipedia",
"dataset:bookcorpus",
"arxiv:1907.11692",
"arxiv:2207.14251",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-28T17:01:03+00:00 | [
"1907.11692",
"2207.14251"
] | [
"en"
] | TAGS
#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_78 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us
|
# RoBERTa, Intermediate Checkpoint - Epoch 78
This model is part of our reimplementation of the RoBERTa model,
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randomly initialized weights before the tra... | [
"# RoBERTa, Intermediate Checkpoint - Epoch 78\n\nThis model is part of our reimplementation of the RoBERTa model, \ntrained on Wikipedia and the Book Corpus only.\nWe train this model for almost 100K steps, corresponding to 83 epochs.\nWe provide the 84 checkpoints (including the randomly initialized weights befor... | [
"TAGS\n#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_78 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us \n",
"# RoBERTa, Intermediate Checkpoint - Epoch 78\n\nThis model is part of our... |
fill-mask | transformers |
# RoBERTa, Intermediate Checkpoint - Epoch 79
This model is part of our reimplementation of the [RoBERTa model](https://arxiv.org/abs/1907.11692),
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randoml... | {"language": "en", "license": "mit", "tags": ["roberta-base", "roberta-base-epoch_79"], "datasets": ["wikipedia", "bookcorpus"]} | yanaiela/roberta-base-epoch_79 | null | [
"transformers",
"pytorch",
"roberta",
"fill-mask",
"roberta-base",
"roberta-base-epoch_79",
"en",
"dataset:wikipedia",
"dataset:bookcorpus",
"arxiv:1907.11692",
"arxiv:2207.14251",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-28T17:02:16+00:00 | [
"1907.11692",
"2207.14251"
] | [
"en"
] | TAGS
#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_79 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us
|
# RoBERTa, Intermediate Checkpoint - Epoch 79
This model is part of our reimplementation of the RoBERTa model,
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randomly initialized weights before the tra... | [
"# RoBERTa, Intermediate Checkpoint - Epoch 79\n\nThis model is part of our reimplementation of the RoBERTa model, \ntrained on Wikipedia and the Book Corpus only.\nWe train this model for almost 100K steps, corresponding to 83 epochs.\nWe provide the 84 checkpoints (including the randomly initialized weights befor... | [
"TAGS\n#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_79 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us \n",
"# RoBERTa, Intermediate Checkpoint - Epoch 79\n\nThis model is part of our... |
token-classification | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# xlm-roberta-base-finetuned-panx-de
This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-b... | {"license": "mit", "tags": ["generated_from_trainer"], "datasets": ["xtreme"], "model-index": [{"name": "xlm-roberta-base-finetuned-panx-de", "results": []}]} | carblacac/xlm-roberta-base-finetuned-panx-de | null | [
"transformers",
"pytorch",
"tensorboard",
"xlm-roberta",
"token-classification",
"generated_from_trainer",
"dataset:xtreme",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-28T17:02:50+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #xlm-roberta #token-classification #generated_from_trainer #dataset-xtreme #license-mit #autotrain_compatible #endpoints_compatible #region-us
|
# xlm-roberta-base-finetuned-panx-de
This model is a fine-tuned version of xlm-roberta-base on the xtreme dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hy... | [
"# xlm-roberta-base-finetuned-panx-de\n\nThis model is a fine-tuned version of xlm-roberta-base on the xtreme dataset.",
"## Model description\n\nMore information needed",
"## Intended uses & limitations\n\nMore information needed",
"## Training and evaluation data\n\nMore information needed",
"## Training ... | [
"TAGS\n#transformers #pytorch #tensorboard #xlm-roberta #token-classification #generated_from_trainer #dataset-xtreme #license-mit #autotrain_compatible #endpoints_compatible #region-us \n",
"# xlm-roberta-base-finetuned-panx-de\n\nThis model is a fine-tuned version of xlm-roberta-base on the xtreme dataset.",
... |
fill-mask | transformers |
# RoBERTa, Intermediate Checkpoint - Epoch 80
This model is part of our reimplementation of the [RoBERTa model](https://arxiv.org/abs/1907.11692),
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randoml... | {"language": "en", "license": "mit", "tags": ["roberta-base", "roberta-base-epoch_80"], "datasets": ["wikipedia", "bookcorpus"]} | yanaiela/roberta-base-epoch_80 | null | [
"transformers",
"pytorch",
"roberta",
"fill-mask",
"roberta-base",
"roberta-base-epoch_80",
"en",
"dataset:wikipedia",
"dataset:bookcorpus",
"arxiv:1907.11692",
"arxiv:2207.14251",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-28T17:03:25+00:00 | [
"1907.11692",
"2207.14251"
] | [
"en"
] | TAGS
#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_80 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us
|
# RoBERTa, Intermediate Checkpoint - Epoch 80
This model is part of our reimplementation of the RoBERTa model,
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randomly initialized weights before the tra... | [
"# RoBERTa, Intermediate Checkpoint - Epoch 80\n\nThis model is part of our reimplementation of the RoBERTa model, \ntrained on Wikipedia and the Book Corpus only.\nWe train this model for almost 100K steps, corresponding to 83 epochs.\nWe provide the 84 checkpoints (including the randomly initialized weights befor... | [
"TAGS\n#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_80 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us \n",
"# RoBERTa, Intermediate Checkpoint - Epoch 80\n\nThis model is part of our... |
fill-mask | transformers |
# RoBERTa, Intermediate Checkpoint - Epoch 81
This model is part of our reimplementation of the [RoBERTa model](https://arxiv.org/abs/1907.11692),
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randoml... | {"language": "en", "license": "mit", "tags": ["roberta-base", "roberta-base-epoch_81"], "datasets": ["wikipedia", "bookcorpus"]} | yanaiela/roberta-base-epoch_81 | null | [
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|
# RoBERTa, Intermediate Checkpoint - Epoch 81
This model is part of our reimplementation of the RoBERTa model,
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randomly initialized weights before the tra... | [
"# RoBERTa, Intermediate Checkpoint - Epoch 81\n\nThis model is part of our reimplementation of the RoBERTa model, \ntrained on Wikipedia and the Book Corpus only.\nWe train this model for almost 100K steps, corresponding to 83 epochs.\nWe provide the 84 checkpoints (including the randomly initialized weights befor... | [
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fill-mask | transformers |
# RoBERTa, Intermediate Checkpoint - Epoch 82
This model is part of our reimplementation of the [RoBERTa model](https://arxiv.org/abs/1907.11692),
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randoml... | {"language": "en", "license": "mit", "tags": ["roberta-base", "roberta-base-epoch_82"], "datasets": ["wikipedia", "bookcorpus"]} | yanaiela/roberta-base-epoch_82 | null | [
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|
# RoBERTa, Intermediate Checkpoint - Epoch 82
This model is part of our reimplementation of the RoBERTa model,
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randomly initialized weights before the tra... | [
"# RoBERTa, Intermediate Checkpoint - Epoch 82\n\nThis model is part of our reimplementation of the RoBERTa model, \ntrained on Wikipedia and the Book Corpus only.\nWe train this model for almost 100K steps, corresponding to 83 epochs.\nWe provide the 84 checkpoints (including the randomly initialized weights befor... | [
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"# RoBERTa, Intermediate Checkpoint - Epoch 82\n\nThis model is part of our... |
fill-mask | transformers |
# RoBERTa, Intermediate Checkpoint - Epoch 83
This model is part of our reimplementation of the [RoBERTa model](https://arxiv.org/abs/1907.11692),
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randoml... | {"language": "en", "license": "mit", "tags": ["roberta-base", "roberta-base-epoch_83"], "datasets": ["wikipedia", "bookcorpus"]} | yanaiela/roberta-base-epoch_83 | null | [
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|
# RoBERTa, Intermediate Checkpoint - Epoch 83
This model is part of our reimplementation of the RoBERTa model,
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randomly initialized weights before the tra... | [
"# RoBERTa, Intermediate Checkpoint - Epoch 83\n\nThis model is part of our reimplementation of the RoBERTa model, \ntrained on Wikipedia and the Book Corpus only.\nWe train this model for almost 100K steps, corresponding to 83 epochs.\nWe provide the 84 checkpoints (including the randomly initialized weights befor... | [
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"# RoBERTa, Intermediate Checkpoint - Epoch 83\n\nThis model is part of our... |
text-generation | transformers |
# DialoGPT BaymaxBot | {"tags": ["conversational"]} | lizz27/DialoGPT-medium-BaymaxBot | null | [
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null | null |
<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->
# Heem/distilroberta-finetuned-wtner
This model is a fine-tuned version of [distilroberta-base](https://huggingface.co/distilroberta-bas... | {"license": "apache-2.0", "tags": ["generated_from_keras_callback"], "model-index": [{"name": "Heem/distilroberta-finetuned-wtner", "results": []}]} | Heem/distilroberta-finetuned-wtner | null | [
"generated_from_keras_callback",
"license:apache-2.0",
"region:us"
] | null | 2022-07-28T17:07:20+00:00 | [] | [] | TAGS
#generated_from_keras_callback #license-apache-2.0 #region-us
| Heem/distilroberta-finetuned-wtner
==================================
This model is a fine-tuned version of distilroberta-base on an unknown dataset.
It achieves the following results on the evaluation set:
* Train Loss: 0.0055
* Validation Loss: 0.4521
* Train Precision: 0.7410
* Train Recall: 0.8122
* Train F1: 0... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* optimizer: {'name': 'AdamWeightDecay', 'learning\\_rate': {'class\\_name': 'PolynomialDecay', 'config': {'initial\\_learning\\_rate': 2e-05, 'decay\\_steps': 2030, 'end\\_learning\\_rate': 0.0, 'power': 1.0, 'cycle': ... | [
"TAGS\n#generated_from_keras_callback #license-apache-2.0 #region-us \n",
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text-generation | transformers |
# DialoGPT BaymaxBot
| {"tags": ["conversational"]} | soop/DialoGPT-medium-BaymaxBot | null | [
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|
# DialoGPT BaymaxBot
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text-generation | transformers |
# DialoGPT BaymaxBot | {"tags": ["conversational"]} | abelblue3/DialoGPT-medium-baymax | null | [
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# DialoGPT BaymaxBot | [
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text-generation | transformers |
#DialoGPT BaymaxBot | {"tags": ["conversational"]} | priyankac/DialoGPT-medium-BaymaxBot | null | [
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] | null | 2022-07-28T17:10:18+00:00 | [] | [] | TAGS
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#DialoGPT BaymaxBot | [] | [
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fill-mask | transformers |
# RoBERTa, Intermediate Checkpoint - Epoch 0
This model is part of our reimplementation of the [RoBERTa model](https://arxiv.org/abs/1907.11692),
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randomly... | {"language": "en", "license": "mit", "tags": ["roberta-base", "roberta-base-epoch_0"], "datasets": ["wikipedia", "bookcorpus"]} | yanaiela/roberta-base-epoch_0 | null | [
"transformers",
"pytorch",
"roberta",
"fill-mask",
"roberta-base",
"roberta-base-epoch_0",
"en",
"dataset:wikipedia",
"dataset:bookcorpus",
"arxiv:1907.11692",
"arxiv:2207.14251",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-28T17:33:20+00:00 | [
"1907.11692",
"2207.14251"
] | [
"en"
] | TAGS
#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_0 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us
|
# RoBERTa, Intermediate Checkpoint - Epoch 0
This model is part of our reimplementation of the RoBERTa model,
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randomly initialized weights before the trai... | [
"# RoBERTa, Intermediate Checkpoint - Epoch 0\n\nThis model is part of our reimplementation of the RoBERTa model, \ntrained on Wikipedia and the Book Corpus only.\nWe train this model for almost 100K steps, corresponding to 83 epochs.\nWe provide the 84 checkpoints (including the randomly initialized weights before... | [
"TAGS\n#transformers #pytorch #roberta #fill-mask #roberta-base #roberta-base-epoch_0 #en #dataset-wikipedia #dataset-bookcorpus #arxiv-1907.11692 #arxiv-2207.14251 #license-mit #autotrain_compatible #endpoints_compatible #region-us \n",
"# RoBERTa, Intermediate Checkpoint - Epoch 0\n\nThis model is part of our r... |
image-classification | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# platzi-vit-base-beans
This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vi... | {"license": "apache-2.0", "tags": ["image-classification", "generated_from_trainer"], "datasets": ["beans"], "metrics": ["accuracy"], "widget": [{"src": "https://huggingface.co/platzi/platzi-vit-base-beans/resolve/main/healthy.jpeg", "example_title": "Healthy"}, {"src": "https://huggingface.co/platzi/platzi-vit-base-be... | platzi/platzi-vit-base-beans-omar-espejel | null | [
"transformers",
"pytorch",
"tensorboard",
"vit",
"image-classification",
"generated_from_trainer",
"dataset:beans",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-28T17:37:49+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #vit #image-classification #generated_from_trainer #dataset-beans #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us
| platzi-vit-base-beans
=====================
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the beans dataset.
It achieves the following results on the evaluation set:
* Loss: 0.0336
* Accuracy: 0.9925
Model description
-----------------
More information needed
Intended uses & limit... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0002\n* train\\_batch\\_size: 8\n* eval\\_batch\\_size: 8\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 4",
"### Trainin... | [
"TAGS\n#transformers #pytorch #tensorboard #vit #image-classification #generated_from_trainer #dataset-beans #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_ra... |
text-classification | transformers |
## What is Roberta-Earning-Call-Transcript-Classification Model?
Roberta-Earning-Call-Transcript-Classification is a Multi-Label Classification Model trained with Annotated earning call transcript data. Roberta-base model was fine-tuned to train on earning call transcript data. This model could be very helpful in fin... | {"widget": [{"text": "Paytm\u2019s Revenue Growth Trajectory To Remain Strong In Q1: Goldman Sachs"}, {"text": "Nifty ends above 16,900, Sensex gains 1,041 pts led by IT, metal, realty"}, {"text": "Amazon reports BLOWOUT earnings, beating revenue estimates and raising Q3 guidance"}, {"text": "Company went through great... | NLPScholars/Roberta-Earning-Call-Transcript-Classification | null | [
"transformers",
"pytorch",
"roberta",
"text-classification",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-28T17:53:45+00:00 | [] | [] | TAGS
#transformers #pytorch #roberta #text-classification #autotrain_compatible #endpoints_compatible #region-us
| What is Roberta-Earning-Call-Transcript-Classification Model?
-------------------------------------------------------------
Roberta-Earning-Call-Transcript-Classification is a Multi-Label Classification Model trained with Annotated earning call transcript data. Roberta-base model was fine-tuned to train on earning ca... | [] | [
"TAGS\n#transformers #pytorch #roberta #text-classification #autotrain_compatible #endpoints_compatible #region-us \n"
] |
text-classification | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# distilbert-base-uncased-finetuned-emotion
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["emotion"], "metrics": ["accuracy", "f1"], "model-index": [{"name": "distilbert-base-uncased-finetuned-emotion", "results": [{"task": {"type": "text-classification", "name": "Text Classification"}, "dataset": {"name": "emotion", "type": "emotion... | liujxing/distilbert-base-uncased-finetuned-emotion | null | [
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"tensorboard",
"distilbert",
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"generated_from_trainer",
"dataset:emotion",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-28T19:37:58+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #distilbert #text-classification #generated_from_trainer #dataset-emotion #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us
| distilbert-base-uncased-finetuned-emotion
=========================================
This model is a fine-tuned version of distilbert-base-uncased on the emotion dataset.
It achieves the following results on the evaluation set:
* Loss: 0.1484
* Accuracy: 0.9355
* F1: 0.9359
Model description
-----------------
Mo... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\n* train\\_batch\\_size: 64\n* eval\\_batch\\_size: 64\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 2",
"### Traini... | [
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"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learn... |
translation | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# Zu-En_update
This model is a fine-tuned version of [kabelomalapane/model_zu-en_updated](https://huggingface.co/kabelomalapane/mo... | {"license": "apache-2.0", "tags": ["translation", "generated_from_trainer"], "metrics": ["bleu"], "model-index": [{"name": "Zu-En_update", "results": []}]} | kabelomalapane/Zu-En_update | null | [
"transformers",
"pytorch",
"tensorboard",
"marian",
"text2text-generation",
"translation",
"generated_from_trainer",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-28T19:40:35+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #marian #text2text-generation #translation #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
| Zu-En\_update
=============
This model is a fine-tuned version of kabelomalapane/model\_zu-en\_updated on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 1.9399
* Bleu: 27.9608
Model description
-----------------
More information needed
Intended uses & limitations
----------... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 32\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 10",
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text-generation | null |
#Artoria testing bot | {"tags": ["conversational"]} | Ironpanther1/Testing | null | [
"conversational",
"region:us"
] | null | 2022-07-28T19:44:33+00:00 | [] | [] | TAGS
#conversational #region-us
|
#Artoria testing bot | [] | [
"TAGS\n#conversational #region-us \n"
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null | fastai |
# Amazing!
🥳 Congratulations on hosting your fastai model on the Hugging Face Hub!
# Some next steps
1. Fill out this model card with more information (see the template below and the [documentation here](https://huggingface.co/docs/hub/model-repos))!
2. Create a demo in Gradio or Streamlit using 🤗 Spaces ([docume... | {"tags": ["fastai"]} | tompham97/clothe-classifier | null | [
"fastai",
"region:us"
] | null | 2022-07-28T19:59:38+00:00 | [] | [] | TAGS
#fastai #region-us
|
# Amazing!
Congratulations on hosting your fastai model on the Hugging Face Hub!
# Some next steps
1. Fill out this model card with more information (see the template below and the documentation here)!
2. Create a demo in Gradio or Streamlit using Spaces (documentation here).
3. Join the fastai community on the ... | [
"# Amazing!\n\n Congratulations on hosting your fastai model on the Hugging Face Hub!",
"# Some next steps\n1. Fill out this model card with more information (see the template below and the documentation here)!\n\n2. Create a demo in Gradio or Streamlit using Spaces (documentation here).\n\n3. Join the fastai co... | [
"TAGS\n#fastai #region-us \n",
"# Amazing!\n\n Congratulations on hosting your fastai model on the Hugging Face Hub!",
"# Some next steps\n1. Fill out this model card with more information (see the template below and the documentation here)!\n\n2. Create a demo in Gradio or Streamlit using Spaces (documentatio... |
question-answering | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# roberta-base-spanish-squades-becasIncentivos6
This model is a fine-tuned version of [IIC/roberta-base-spanish-squades](https://h... | {"tags": ["generated_from_trainer"], "datasets": ["becasv2"], "model-index": [{"name": "roberta-base-spanish-squades-becasIncentivos6", "results": []}]} | Evelyn18/roberta-base-spanish-squades-becasIncentivos6 | null | [
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"tensorboard",
"roberta",
"question-answering",
"generated_from_trainer",
"dataset:becasv2",
"endpoints_compatible",
"region:us"
] | null | 2022-07-28T20:08:34+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #roberta #question-answering #generated_from_trainer #dataset-becasv2 #endpoints_compatible #region-us
| roberta-base-spanish-squades-becasIncentivos6
=============================================
This model is a fine-tuned version of IIC/roberta-base-spanish-squades on the becasv2 dataset.
It achieves the following results on the evaluation set:
* Loss: 2.0023
Model description
-----------------
More information ... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 3e-05\n* train\\_batch\\_size: 32\n* eval\\_batch\\_size: 32\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 6",
"### Traini... | [
"TAGS\n#transformers #pytorch #tensorboard #roberta #question-answering #generated_from_trainer #dataset-becasv2 #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 3e-05\n* train\\_batch\\_size: 32\n* eval\\_bat... |
token-classification | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# movieHunt3-ner
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) o... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "model-index": [{"name": "movieHunt3-ner", "results": []}]} | AbidHasan95/movieHunt3-ner | null | [
"transformers",
"pytorch",
"tensorboard",
"distilbert",
"token-classification",
"generated_from_trainer",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-28T20:30:57+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #distilbert #token-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
| movieHunt3-ner
==============
This model is a fine-tuned version of distilbert-base-uncased on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 0.0009
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More in... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 10",
"### Train... | [
"TAGS\n#transformers #pytorch #tensorboard #distilbert #token-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_... |
fill-mask | transformers | # Tranception model
This Hugging Face Hub repo contains the model checkpoint for the Tranception model as described in our paper ["Tranception: protein fitness prediction with autoregressive transformers and inference-time retrieval"](https://arxiv.org/abs/2205.13760). The official GitHub repository can be accessed [h... | {} | ICML2022/Tranception | null | [
"transformers",
"pytorch",
"tranception",
"fill-mask",
"arxiv:2205.13760",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-28T21:27:55+00:00 | [
"2205.13760"
] | [] | TAGS
#transformers #pytorch #tranception #fill-mask #arxiv-2205.13760 #autotrain_compatible #endpoints_compatible #region-us
| # Tranception model
This Hugging Face Hub repo contains the model checkpoint for the Tranception model as described in our paper "Tranception: protein fitness prediction with autoregressive transformers and inference-time retrieval". The official GitHub repository can be accessed here. This project is a joint collabor... | [
"# Tranception model\n\nThis Hugging Face Hub repo contains the model checkpoint for the Tranception model as described in our paper \"Tranception: protein fitness prediction with autoregressive transformers and inference-time retrieval\". The official GitHub repository can be accessed here. This project is a joint... | [
"TAGS\n#transformers #pytorch #tranception #fill-mask #arxiv-2205.13760 #autotrain_compatible #endpoints_compatible #region-us \n",
"# Tranception model\n\nThis Hugging Face Hub repo contains the model checkpoint for the Tranception model as described in our paper \"Tranception: protein fitness prediction with au... |
text2text-generation | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# bert-small2bert-small-finetuned-cnn_daily_mail-summarization-finetuned-bbc-news-Sumy
This model is a fine-tuned version of [mrm8... | {"license": "apache-2.0", "tags": ["summarisation", "generated_from_trainer"], "metrics": ["rouge"], "model-index": [{"name": "bert-small2bert-small-finetuned-cnn_daily_mail-summarization-finetuned-bbc-news-Sumy", "results": []}]} | Atharvgarg/bert-small2bert-small-finetuned-cnn_daily_mail-summarization-finetuned-bbc-news-Sumy | null | [
"transformers",
"pytorch",
"tensorboard",
"encoder-decoder",
"text2text-generation",
"summarisation",
"generated_from_trainer",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-28T21:51:50+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #encoder-decoder #text2text-generation #summarisation #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
| bert-small2bert-small-finetuned-cnn\_daily\_mail-summarization-finetuned-bbc-news-Sumy
======================================================================================
This model is a fine-tuned version of mrm8488/bert-small2bert-small-finetuned-cnn\_daily\_mail-summarization on an unknown dataset.
It achieves ... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5.6e-05\n* train\\_batch\\_size: 8\n* eval\\_batch\\_size: 8\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 8",
"### Traini... | [
"TAGS\n#transformers #pytorch #tensorboard #encoder-decoder #text2text-generation #summarisation #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rat... |
reinforcement-learning | sample-factory |
A(n) **APPO** model trained on the **atari_pong** environment.
This model was trained using Sample Factory 2.0: https://github.com/alex-petrenko/sample-factory
| {"library_name": "sample-factory", "tags": ["deep-reinforcement-learning", "reinforcement-learning", "sample-factory"], "model-index": [{"name": "APPO", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "atari_pong", "type": "atari_pong"}, "metrics": [{"type"... | wmFrank/sample-factory-2-atari-pong | null | [
"sample-factory",
"tensorboard",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-07-28T22:04:49+00:00 | [] | [] | TAGS
#sample-factory #tensorboard #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
A(n) APPO model trained on the atari_pong environment.
This model was trained using Sample Factory 2.0: URL
| [] | [
"TAGS\n#sample-factory #tensorboard #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n"
] |
reinforcement-learning | sample-factory |
A(n) **APPO** model trained on the **atari_beamrider** environment.
This model was trained using Sample Factory 2.0: https://github.com/alex-petrenko/sample-factory
| {"library_name": "sample-factory", "tags": ["deep-reinforcement-learning", "reinforcement-learning", "sample-factory"], "model-index": [{"name": "APPO", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "atari_beamrider", "type": "atari_beamrider"}, "metrics"... | wmFrank/sample-factory-2-atari-beamrider | null | [
"sample-factory",
"tensorboard",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-07-28T22:08:32+00:00 | [] | [] | TAGS
#sample-factory #tensorboard #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
A(n) APPO model trained on the atari_beamrider environment.
This model was trained using Sample Factory 2.0: URL
| [] | [
"TAGS\n#sample-factory #tensorboard #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n"
] |
reinforcement-learning | sample-factory |
A(n) **APPO** model trained on the **atari_breakout** environment.
This model was trained using Sample Factory 2.0: https://github.com/alex-petrenko/sample-factory
| {"library_name": "sample-factory", "tags": ["deep-reinforcement-learning", "reinforcement-learning", "sample-factory"], "model-index": [{"name": "APPO", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "atari_breakout", "type": "atari_breakout"}, "metrics": ... | wmFrank/sample-factory-2-atari-breakout | null | [
"sample-factory",
"tensorboard",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-07-28T22:10:36+00:00 | [] | [] | TAGS
#sample-factory #tensorboard #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
A(n) APPO model trained on the atari_breakout environment.
This model was trained using Sample Factory 2.0: URL
| [] | [
"TAGS\n#sample-factory #tensorboard #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n"
] |
audio-to-audio | espnet |
## ESPnet2 ENH model
### `espnet/Yen-Ju_Lu_l3das22_enh_train_enh_ineube_valid.loss.ave`
This model was trained by neillu23 using l3das22 recipe in [espnet](https://github.com/espnet/espnet/).
### Demo: How to use in ESPnet2
```bash
cd espnet
git checkout 11d687844a544fcce6f6d0ce7a0a302e0e47d442
pip install -e .
c... | {"language": "en", "license": "cc-by-4.0", "tags": ["espnet", "audio", "audio-to-audio"], "datasets": ["l3das22"]} | espnet/Yen-Ju_Lu_l3das22_enh_train_enh_ineube_valid.loss.ave | null | [
"espnet",
"audio",
"audio-to-audio",
"en",
"dataset:l3das22",
"arxiv:1804.00015",
"license:cc-by-4.0",
"region:us"
] | null | 2022-07-28T22:28:46+00:00 | [
"1804.00015"
] | [
"en"
] | TAGS
#espnet #audio #audio-to-audio #en #dataset-l3das22 #arxiv-1804.00015 #license-cc-by-4.0 #region-us
| ESPnet2 ENH model
-----------------
### 'espnet/Yen-Ju\_Lu\_l3das22\_enh\_train\_enh\_ineube\_valid.URL'
This model was trained by neillu23 using l3das22 recipe in espnet.
### Demo: How to use in ESPnet2
RESULTS
=======
Environments
------------
* date: 'Wed Jul 6 20:46:10 UTC 2022'
* python version: '3.8.1... | [
"### 'espnet/Yen-Ju\\_Lu\\_l3das22\\_enh\\_train\\_enh\\_ineube\\_valid.URL'\n\n\nThis model was trained by neillu23 using l3das22 recipe in espnet.",
"### Demo: How to use in ESPnet2\n\n\nRESULTS\n=======\n\n\nEnvironments\n------------\n\n\n* date: 'Wed Jul 6 20:46:10 UTC 2022'\n* python version: '3.8.13 (defau... | [
"TAGS\n#espnet #audio #audio-to-audio #en #dataset-l3das22 #arxiv-1804.00015 #license-cc-by-4.0 #region-us \n",
"### 'espnet/Yen-Ju\\_Lu\\_l3das22\\_enh\\_train\\_enh\\_ineube\\_valid.URL'\n\n\nThis model was trained by neillu23 using l3das22 recipe in espnet.",
"### Demo: How to use in ESPnet2\n\n\nRESULTS\n==... |
summarization | transformers |
# Validation Metrics
- Loss: 2.133
- Rouge1: 45.861
- Rouge2: 14.179
- RougeL: 23.565
- RougeLsum: 40.908
- Gen Len: 195.334 | {"language": ["en"], "tags": ["summarization"], "datasets": ["Blaise-g/autotrain-data-SumPubmed", "Blaise-g/SumPubmed"], "widget": [{"text": "Biomedical paper of choice \ud83e\udd17"}], "co2_eq_emissions": {"emissions": 1027.9}, "model-index": [{"name": "Blaise-g/led_pubmed_sumpubmed_1", "results": [{"task": {"type": "... | Blaise-g/led_pubmed_sumpubmed_1 | null | [
"transformers",
"pytorch",
"safetensors",
"led",
"text2text-generation",
"summarization",
"en",
"dataset:Blaise-g/autotrain-data-SumPubmed",
"dataset:Blaise-g/SumPubmed",
"model-index",
"co2_eq_emissions",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-28T23:41:04+00:00 | [] | [
"en"
] | TAGS
#transformers #pytorch #safetensors #led #text2text-generation #summarization #en #dataset-Blaise-g/autotrain-data-SumPubmed #dataset-Blaise-g/SumPubmed #model-index #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us
|
# Validation Metrics
- Loss: 2.133
- Rouge1: 45.861
- Rouge2: 14.179
- RougeL: 23.565
- RougeLsum: 40.908
- Gen Len: 195.334 | [
"# Validation Metrics\n\n- Loss: 2.133\n- Rouge1: 45.861\n- Rouge2: 14.179\n- RougeL: 23.565\n- RougeLsum: 40.908\n- Gen Len: 195.334"
] | [
"TAGS\n#transformers #pytorch #safetensors #led #text2text-generation #summarization #en #dataset-Blaise-g/autotrain-data-SumPubmed #dataset-Blaise-g/SumPubmed #model-index #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us \n",
"# Validation Metrics\n\n- Loss: 2.133\n- Rouge1: 45.861\n- Rou... |
token-classification | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# ADE-Bio_ClinicalBERT-NER
This model is a fine-tuned version of [emilyalsentzer/Bio_ClinicalBERT](https://huggingface.co/emilyals... | {"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["precision", "recall", "f1", "accuracy"], "model-index": [{"name": "ADE-Bio_ClinicalBERT-NER", "results": []}]} | commanderstrife/ADE-Bio_ClinicalBERT-NER | null | [
"transformers",
"pytorch",
"tensorboard",
"bert",
"token-classification",
"generated_from_trainer",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-29T00:24:29+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #bert #token-classification #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #region-us
| ADE-Bio\_ClinicalBERT-NER
=========================
This model is a fine-tuned version of emilyalsentzer/Bio\_ClinicalBERT on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.1926
* Precision: 0.7830
* Recall: 0.8811
* F1: 0.8291
* Accuracy: 0.9437
Model description
---------... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 1e-05\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 5",
"### Traini... | [
"TAGS\n#transformers #pytorch #tensorboard #bert #token-classification #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 1e-05\n* train\\_batch\\_size:... |
reinforcement-learning | stable-baselines3 |
# **A2C** Agent playing **AntBulletEnv-v0**
This is a trained model of a **A2C** agent playing **AntBulletEnv-v0**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
## Usage (with Stable-baselines3)
TODO: Add your code
```python
from stable_baselines3 import ...
from huggingface_sb... | {"library_name": "stable-baselines3", "tags": ["AntBulletEnv-v0", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "A2C", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "AntBulletEnv-v0", "type": "AntB... | jianzhnie/a2c-AntBulletEnv-v0 | null | [
"stable-baselines3",
"tensorboard",
"AntBulletEnv-v0",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-07-29T01:15:51+00:00 | [] | [] | TAGS
#stable-baselines3 #tensorboard #AntBulletEnv-v0 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# A2C Agent playing AntBulletEnv-v0
This is a trained model of a A2C agent playing AntBulletEnv-v0
using the stable-baselines3 library.
## Usage (with Stable-baselines3)
TODO: Add your code
| [
"# A2C Agent playing AntBulletEnv-v0\nThis is a trained model of a A2C agent playing AntBulletEnv-v0\nusing the stable-baselines3 library.",
"## Usage (with Stable-baselines3)\nTODO: Add your code"
] | [
"TAGS\n#stable-baselines3 #tensorboard #AntBulletEnv-v0 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# A2C Agent playing AntBulletEnv-v0\nThis is a trained model of a A2C agent playing AntBulletEnv-v0\nusing the stable-baselines3 library.",
"## Usage (with Stable-baselines3... |
text-generation | transformers |
<div class="inline-flex flex-col" style="line-height: 1.5;">
<div class="flex">
<div
style="display:inherit; margin-left: 4px; margin-right: 4px; width: 92px; height:92px; border-radius: 50%; background-size: cover; background-image: url('https://pbs.twimg.com/profile_images/1640242374264729600/egMD... | {"language": "en", "tags": ["huggingtweets"], "thumbnail": "https://github.com/borisdayma/huggingtweets/blob/master/img/logo.png?raw=true", "widget": [{"text": "My dream is"}]} | huggingtweets/ottorothmund | null | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"huggingtweets",
"en",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-07-29T01:16:58+00:00 | [] | [
"en"
] | TAGS
#transformers #pytorch #gpt2 #text-generation #huggingtweets #en #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
AI BOT
OTTO ︎
@ottorothmund
I was made with huggingtweets.
Create your own bot based on your favorite user with the demo!
How does it work?
-----------------
The model uses the following pipeline.
!pipeline
To understand how the model was developed, check the W&B report.
Training data
------------... | [] | [
"TAGS\n#transformers #pytorch #gpt2 #text-generation #huggingtweets #en #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n"
] |
text2text-generation | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# c-deobfuscate-mt
This model is a fine-tuned version of [Salesforce/codet5-base](https://huggingface.co/Salesforce/codet5-base) o... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "model-index": [{"name": "c-deobfuscate-mt", "results": []}]} | ckb/c-deobfuscate-mt | null | [
"transformers",
"pytorch",
"tensorboard",
"safetensors",
"t5",
"text2text-generation",
"generated_from_trainer",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-07-29T01:27:00+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #safetensors #t5 #text2text-generation #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# c-deobfuscate-mt
This model is a fine-tuned version of Salesforce/codet5-base on an unknown dataset.
It achieves the following results on the evaluation set:
- eval_loss: 0.5207
- eval_bleu: 65.8038
- eval_gen_len: 266.6
- eval_runtime: 13.5258
- eval_samples_per_second: 1.109
- eval_steps_per_second: 0.148
- epo... | [
"# c-deobfuscate-mt\n\nThis model is a fine-tuned version of Salesforce/codet5-base on an unknown dataset.\nIt achieves the following results on the evaluation set:\n- eval_loss: 0.5207\n- eval_bleu: 65.8038\n- eval_gen_len: 266.6\n- eval_runtime: 13.5258\n- eval_samples_per_second: 1.109\n- eval_steps_per_second: ... | [
"TAGS\n#transformers #pytorch #tensorboard #safetensors #t5 #text2text-generation #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
"# c-deobfuscate-mt\n\nThis model is a fine-tuned version of Salesforce/codet5-base on an unknown dat... |
token-classification | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# test_ner3
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["pv_dataset"], "metrics": ["precision", "recall", "f1", "accuracy"], "model-index": [{"name": "test_ner3", "results": [{"task": {"type": "token-classification", "name": "Token Classification"}, "dataset": {"name": "pv_dataset", "type": "pv_datas... | chintagunta85/test_ner3 | null | [
"transformers",
"pytorch",
"tensorboard",
"distilbert",
"token-classification",
"generated_from_trainer",
"dataset:pv_dataset",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-29T01:46:44+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #distilbert #token-classification #generated_from_trainer #dataset-pv_dataset #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us
| test\_ner3
==========
This model is a fine-tuned version of distilbert-base-uncased on the pv\_dataset dataset.
It achieves the following results on the evaluation set:
* Loss: 0.2983
* Precision: 0.6698
* Recall: 0.6499
* F1: 0.6597
* Accuracy: 0.9607
Model description
-----------------
More information needed... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 20",
"### Train... | [
"TAGS\n#transformers #pytorch #tensorboard #distilbert #token-classification #generated_from_trainer #dataset-pv_dataset #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* l... |
feature-extraction | transformers | # relbert/roberta-large-conceptnet-average-prompt-b-nce
RelBERT fine-tuned from [roberta-large](https://huggingface.co/roberta-large) on
[relbert/conceptnet_high_confidence](https://huggingface.co/datasets/relbert/conceptnet_high_confidence).
Fine-tuning is done via [RelBERT](https://github.com/asahi417/relbert) lib... | {"datasets": ["relbert/conceptnet_high_confidence"], "model-index": [{"name": "relbert/roberta-large-conceptnet-average-prompt-b-nce", "results": [{"task": {"type": "sorting-task", "name": "Relation Mapping"}, "dataset": {"name": "Relation Mapping", "type": "relation-mapping", "args": "relbert/relation_mapping"}, "metr... | research-backup/roberta-large-conceptnet-average-prompt-b-nce | null | [
"transformers",
"pytorch",
"roberta",
"feature-extraction",
"dataset:relbert/conceptnet_high_confidence",
"model-index",
"endpoints_compatible",
"region:us"
] | null | 2022-07-29T02:34:21+00:00 | [] | [] | TAGS
#transformers #pytorch #roberta #feature-extraction #dataset-relbert/conceptnet_high_confidence #model-index #endpoints_compatible #region-us
| # relbert/roberta-large-conceptnet-average-prompt-b-nce
RelBERT fine-tuned from roberta-large on
relbert/conceptnet_high_confidence.
Fine-tuning is done via RelBERT library (see the repository for more detail).
It achieves the following results on the relation understanding tasks:
- Analogy Question (dataset, full r... | [
"# relbert/roberta-large-conceptnet-average-prompt-b-nce\n\nRelBERT fine-tuned from roberta-large on \nrelbert/conceptnet_high_confidence.\nFine-tuning is done via RelBERT library (see the repository for more detail).\nIt achieves the following results on the relation understanding tasks:\n- Analogy Question (data... | [
"TAGS\n#transformers #pytorch #roberta #feature-extraction #dataset-relbert/conceptnet_high_confidence #model-index #endpoints_compatible #region-us \n",
"# relbert/roberta-large-conceptnet-average-prompt-b-nce\n\nRelBERT fine-tuned from roberta-large on \nrelbert/conceptnet_high_confidence.\nFine-tuning is done... |
text-classification | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# roberta-base-finetuned-jigsaw-toxic
This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on... | {"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["accuracy", "f1"], "model-index": [{"name": "roberta-base-finetuned-jigsaw-toxic", "results": []}]} | affahrizain/roberta-base-finetuned-jigsaw-toxic | null | [
"transformers",
"pytorch",
"tensorboard",
"roberta",
"text-classification",
"generated_from_trainer",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-29T02:46:08+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #roberta #text-classification #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #region-us
| roberta-base-finetuned-jigsaw-toxic
===================================
This model is a fine-tuned version of roberta-base on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 0.0859
* Accuracy: 0.9747
* F1: 0.9746
Model description
-----------------
More information needed
In... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 3",
"### Trai... | [
"TAGS\n#transformers #pytorch #tensorboard #roberta #text-classification #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_batch\\_siz... |
token-classification | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# roberta_large-chunking_0728_v2
This model is a fine-tuned version of [roberta-large](https://huggingface.co/roberta-large) on an... | {"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["precision", "recall", "f1", "accuracy"], "model-index": [{"name": "roberta_large-chunking_0728_v2", "results": []}]} | mariolinml/roberta_large-chunking_0728_v2 | null | [
"transformers",
"pytorch",
"tensorboard",
"roberta",
"token-classification",
"generated_from_trainer",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-29T03:10:55+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #roberta #token-classification #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #region-us
| roberta\_large-chunking\_0728\_v2
=================================
This model is a fine-tuned version of roberta-large on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.5270
* Precision: 0.6228
* Recall: 0.6467
* F1: 0.6345
* Accuracy: 0.8153
Model description
------------... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 1e-05\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 5",
"### Traini... | [
"TAGS\n#transformers #pytorch #tensorboard #roberta #token-classification #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 1e-05\n* train\\_batch\\_si... |
token-classification | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# wikineural-multilingual-ner-finetuned-ner
This model is a fine-tuned version of [Babelscape/wikineural-multilingual-ner](https:/... | {"license": "cc-by-nc-sa-4.0", "tags": ["generated_from_trainer"], "datasets": ["skript"], "metrics": ["precision", "recall", "f1", "accuracy"], "model-index": [{"name": "wikineural-multilingual-ner-finetuned-ner", "results": [{"task": {"type": "token-classification", "name": "Token Classification"}, "dataset": {"name"... | LanaKru/wikineural-multilingual-ner-finetuned-ner | null | [
"transformers",
"pytorch",
"tensorboard",
"bert",
"token-classification",
"generated_from_trainer",
"dataset:skript",
"license:cc-by-nc-sa-4.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-29T03:14:38+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #bert #token-classification #generated_from_trainer #dataset-skript #license-cc-by-nc-sa-4.0 #model-index #autotrain_compatible #endpoints_compatible #region-us
| wikineural-multilingual-ner-finetuned-ner
=========================================
This model is a fine-tuned version of Babelscape/wikineural-multilingual-ner on the skript dataset.
It achieves the following results on the evaluation set:
* Loss: 0.1243
* Precision: 0.9007
* Recall: 0.9302
* F1: 0.9152
* Accuracy... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 3",
"### Traini... | [
"TAGS\n#transformers #pytorch #tensorboard #bert #token-classification #generated_from_trainer #dataset-skript #license-cc-by-nc-sa-4.0 #model-index #autotrain_compatible #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learni... |
reinforcement-learning | stable-baselines3 |
# **PPO** Agent playing **LunarLander-v2**
This is a trained model of a **PPO** agent playing **LunarLander-v2**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
## Usage (with Stable-baselines3)
TODO: Add your code
```python
from stable_baselines3 import ...
from huggingface_sb3 ... | {"library_name": "stable-baselines3", "tags": ["LunarLander-v2", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "PPO", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "LunarLander-v2", "type": "LunarL... | wpolatkan/ppo-LunarLander-v2 | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-07-29T03:34:31+00:00 | [] | [] | TAGS
#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# PPO Agent playing LunarLander-v2
This is a trained model of a PPO agent playing LunarLander-v2
using the stable-baselines3 library.
## Usage (with Stable-baselines3)
TODO: Add your code
| [
"# PPO Agent playing LunarLander-v2\nThis is a trained model of a PPO agent playing LunarLander-v2\nusing the stable-baselines3 library.",
"## Usage (with Stable-baselines3)\nTODO: Add your code"
] | [
"TAGS\n#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# PPO Agent playing LunarLander-v2\nThis is a trained model of a PPO agent playing LunarLander-v2\nusing the stable-baselines3 library.",
"## Usage (with Stable-baselines3)\nTODO: Add you... |
automatic-speech-recognition | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# wav2vec2-base-timit-demo-google-colab
This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/face... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "model-index": [{"name": "wav2vec2-base-timit-demo-google-colab", "results": []}]} | psroy/wav2vec2-base-timit-demo-google-colab | null | [
"transformers",
"pytorch",
"tensorboard",
"wav2vec2",
"automatic-speech-recognition",
"generated_from_trainer",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-29T03:40:18+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #generated_from_trainer #license-apache-2.0 #endpoints_compatible #region-us
| wav2vec2-base-timit-demo-google-colab
=====================================
This model is a fine-tuned version of facebook/wav2vec2-base on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 0.5366
* Wer: 0.3452
Model description
-----------------
More information needed
Intend... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0001\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 8\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* lr\\_scheduler\\_warmup\\_steps... | [
"TAGS\n#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #generated_from_trainer #license-apache-2.0 #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0001\n* train\\_batch\\_size: 1... |
image-classification | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# swin-tiny-patch4-window7-224-finetuned-eurosat
This model is a fine-tuned version of [microsoft/swin-tiny-patch4-window7-224](ht... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["imagefolder"], "metrics": ["accuracy"], "model-index": [{"name": "swin-tiny-patch4-window7-224-finetuned-eurosat", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type":... | keithanpai/swin-tiny-patch4-window7-224-finetuned-eurosat | null | [
"transformers",
"pytorch",
"tensorboard",
"swin",
"image-classification",
"generated_from_trainer",
"dataset:imagefolder",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-29T03:42:53+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #swin #image-classification #generated_from_trainer #dataset-imagefolder #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us
| swin-tiny-patch4-window7-224-finetuned-eurosat
==============================================
This model is a fine-tuned version of microsoft/swin-tiny-patch4-window7-224 on the imagefolder dataset.
It achieves the following results on the evaluation set:
* Loss: 0.5603
* Accuracy: 0.7914
Model description
------... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\n* train\\_batch\\_size: 32\n* eval\\_batch\\_size: 32\n* seed: 42\n* gradient\\_accumulation\\_steps: 4\n* total\\_train\\_batch\\_size: 128\n* optimizer: Adam with betas=(0.9,0.999) and epsilo... | [
"TAGS\n#transformers #pytorch #tensorboard #swin #image-classification #generated_from_trainer #dataset-imagefolder #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learni... |
feature-extraction | transformers | This Model can be used in the Kaggle Competition - https://www.kaggle.com/competitions/feedback-prize-effectivenes
Data Used to train the MLM model - https://www.kaggle.com/competitions/feedback-prize-2021 | {} | ashishraics/deberta_v3_large_mlm_feedback_prize | null | [
"transformers",
"pytorch",
"deberta-v2",
"feature-extraction",
"endpoints_compatible",
"region:us"
] | null | 2022-07-29T04:05:12+00:00 | [] | [] | TAGS
#transformers #pytorch #deberta-v2 #feature-extraction #endpoints_compatible #region-us
| This Model can be used in the Kaggle Competition - URL
Data Used to train the MLM model - URL | [] | [
"TAGS\n#transformers #pytorch #deberta-v2 #feature-extraction #endpoints_compatible #region-us \n"
] |
reinforcement-learning | stable-baselines3 |
# **A2C** Agent playing **AntBulletEnv-v0**
This is a trained model of a **A2C** agent playing **AntBulletEnv-v0**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
## Usage (with Stable-baselines3)
TODO: Add your code
```python
from stable_baselines3 import ...
from huggingface_sb... | {"library_name": "stable-baselines3", "tags": ["AntBulletEnv-v0", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "A2C", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "AntBulletEnv-v0", "type": "AntB... | jianzhnie/a2c-v1-AntBulletEnv-v0 | null | [
"stable-baselines3",
"tensorboard",
"AntBulletEnv-v0",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-07-29T04:07:17+00:00 | [] | [] | TAGS
#stable-baselines3 #tensorboard #AntBulletEnv-v0 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# A2C Agent playing AntBulletEnv-v0
This is a trained model of a A2C agent playing AntBulletEnv-v0
using the stable-baselines3 library.
## Usage (with Stable-baselines3)
TODO: Add your code
| [
"# A2C Agent playing AntBulletEnv-v0\nThis is a trained model of a A2C agent playing AntBulletEnv-v0\nusing the stable-baselines3 library.",
"## Usage (with Stable-baselines3)\nTODO: Add your code"
] | [
"TAGS\n#stable-baselines3 #tensorboard #AntBulletEnv-v0 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# A2C Agent playing AntBulletEnv-v0\nThis is a trained model of a A2C agent playing AntBulletEnv-v0\nusing the stable-baselines3 library.",
"## Usage (with Stable-baselines3... |
token-classification | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# distilBERT_bio_pv_superset
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-bas... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["precision", "recall", "f1", "accuracy"], "model-index": [{"name": "distilBERT_bio_pv_superset", "results": []}]} | commanderstrife/distilBERT_bio_pv_superset | null | [
"transformers",
"pytorch",
"tensorboard",
"distilbert",
"token-classification",
"generated_from_trainer",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-29T04:41:49+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #distilbert #token-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
| distilBERT\_bio\_pv\_superset
=============================
This model is a fine-tuned version of distilbert-base-uncased on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 0.2328
* Precision: 0.5462
* Recall: 0.5325
* F1: 0.5393
* Accuracy: 0.9495
Model description
------------... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 10",
"### Train... | [
"TAGS\n#transformers #pytorch #tensorboard #distilbert #token-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_... |
reinforcement-learning | stable-baselines3 |
# **PPO** Agent playing **LunarLander-v2**
This is a trained model of a **PPO** agent playing **LunarLander-v2**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
## Usage (with Stable-baselines3)
TODO: Add your code
```python
from stable_baselines3 import ...
from huggingface_sb3 ... | {"library_name": "stable-baselines3", "tags": ["LunarLander-v2", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "PPO", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "LunarLander-v2", "type": "LunarL... | rhiga/ppo-lunar-lander-v2 | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-07-29T04:42:38+00:00 | [] | [] | TAGS
#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# PPO Agent playing LunarLander-v2
This is a trained model of a PPO agent playing LunarLander-v2
using the stable-baselines3 library.
## Usage (with Stable-baselines3)
TODO: Add your code
| [
"# PPO Agent playing LunarLander-v2\nThis is a trained model of a PPO agent playing LunarLander-v2\nusing the stable-baselines3 library.",
"## Usage (with Stable-baselines3)\nTODO: Add your code"
] | [
"TAGS\n#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# PPO Agent playing LunarLander-v2\nThis is a trained model of a PPO agent playing LunarLander-v2\nusing the stable-baselines3 library.",
"## Usage (with Stable-baselines3)\nTODO: Add you... |
image-classification | transformers |
# pond_image_classification_2
Autogenerated by HuggingPics🤗🖼️
Create your own image classifier for **anything** by running [the demo on Google Colab](https://colab.research.google.com/github/nateraw/huggingpics/blob/main/HuggingPics.ipynb).
Report any issues with the demo at the [github repo](https://github.com/... | {"tags": ["image-classification", "pytorch", "huggingpics"], "metrics": ["accuracy"]} | SummerChiam/pond_image_classification_2 | null | [
"transformers",
"pytorch",
"tensorboard",
"vit",
"image-classification",
"huggingpics",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-29T05:23:17+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #vit #image-classification #huggingpics #model-index #autotrain_compatible #endpoints_compatible #region-us
|
# pond_image_classification_2
Autogenerated by HuggingPics️
Create your own image classifier for anything by running the demo on Google Colab.
Report any issues with the demo at the github repo.
## Example Images
#### Algae
!Algae
#### Boiling
!Boiling
#### BoilingNight
!BoilingNight
#### Normal
!Normal... | [
"# pond_image_classification_2\n\n\nAutogenerated by HuggingPics️\n\nCreate your own image classifier for anything by running the demo on Google Colab.\n\nReport any issues with the demo at the github repo.",
"## Example Images",
"#### Algae\n\n!Algae",
"#### Boiling\n\n!Boiling",
"#### BoilingNight\n\n!Boi... | [
"TAGS\n#transformers #pytorch #tensorboard #vit #image-classification #huggingpics #model-index #autotrain_compatible #endpoints_compatible #region-us \n",
"# pond_image_classification_2\n\n\nAutogenerated by HuggingPics️\n\nCreate your own image classifier for anything by running the demo on Google Colab.\n\nRep... |
null | transformers | # ELECTRA discriminator small
- pretrained with large Korean corpus datasets (30GB)
- 13.7M model parameters (followed google/electra-small-discriminator config)
- 32,000 vocab size
- trained for 1,000,000 steps
- build with [lassl](https://github.com/lassl/lassl) framework
pretrain-data
┣ korean_corpus.txt ... | {} | Doohae/lassl-koelectra-small | null | [
"transformers",
"pytorch",
"electra",
"pretraining",
"endpoints_compatible",
"region:us"
] | null | 2022-07-29T05:50:48+00:00 | [] | [] | TAGS
#transformers #pytorch #electra #pretraining #endpoints_compatible #region-us
| # ELECTRA discriminator small
- pretrained with large Korean corpus datasets (30GB)
- 13.7M model parameters (followed google/electra-small-discriminator config)
- 32,000 vocab size
- trained for 1,000,000 steps
- build with lassl framework
pretrain-data
┣ korean_corpus.txt
┣ kowiki_latest.txt
┣ modu_di... | [
"# ELECTRA discriminator small\n- pretrained with large Korean corpus datasets (30GB)\n- 13.7M model parameters (followed google/electra-small-discriminator config)\n- 32,000 vocab size\n- trained for 1,000,000 steps \n- build with lassl framework \n \n\npretrain-data \n ┣ korean_corpus.txt \n ┣ kowiki_latest.t... | [
"TAGS\n#transformers #pytorch #electra #pretraining #endpoints_compatible #region-us \n",
"# ELECTRA discriminator small\n- pretrained with large Korean corpus datasets (30GB)\n- 13.7M model parameters (followed google/electra-small-discriminator config)\n- 32,000 vocab size\n- trained for 1,000,000 steps \n- bui... |
reinforcement-learning | stable-baselines3 |
# **A2C** Agent playing **Walker2DBulletEnv-v0**
This is a trained model of a **A2C** agent playing **Walker2DBulletEnv-v0**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
## Usage (with Stable-baselines3)
TODO: Add your code
```python
from stable_baselines3 import ...
from hugg... | {"library_name": "stable-baselines3", "tags": ["Walker2DBulletEnv-v0", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "A2C", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "Walker2DBulletEnv-v0", "ty... | jianzhnie/a2c-v1-Walker2DBulletEnv-v0 | null | [
"stable-baselines3",
"tensorboard",
"Walker2DBulletEnv-v0",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-07-29T05:52:47+00:00 | [] | [] | TAGS
#stable-baselines3 #tensorboard #Walker2DBulletEnv-v0 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# A2C Agent playing Walker2DBulletEnv-v0
This is a trained model of a A2C agent playing Walker2DBulletEnv-v0
using the stable-baselines3 library.
## Usage (with Stable-baselines3)
TODO: Add your code
| [
"# A2C Agent playing Walker2DBulletEnv-v0\nThis is a trained model of a A2C agent playing Walker2DBulletEnv-v0\nusing the stable-baselines3 library.",
"## Usage (with Stable-baselines3)\nTODO: Add your code"
] | [
"TAGS\n#stable-baselines3 #tensorboard #Walker2DBulletEnv-v0 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# A2C Agent playing Walker2DBulletEnv-v0\nThis is a trained model of a A2C agent playing Walker2DBulletEnv-v0\nusing the stable-baselines3 library.",
"## Usage (with St... |
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