modelId stringlengths 4 111 | lastModified stringlengths 24 24 | tags list | pipeline_tag stringlengths 5 30 ⌀ | author stringlengths 2 34 ⌀ | config null | securityStatus null | id stringlengths 4 111 | likes int64 0 9.53k | downloads int64 2 73.6M | library_name stringlengths 2 84 ⌀ | created timestamp[us] | card stringlengths 101 901k | card_len int64 101 901k | embeddings list |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
gokuls/hBERTv1_new_pretrain_cola | 2023-06-06T06:39:55.000Z | [
"transformers",
"pytorch",
"tensorboard",
"hybridbert",
"text-classification",
"generated_from_trainer",
"en",
"dataset:glue",
"model-index",
"endpoints_compatible",
"region:us"
] | text-classification | gokuls | null | null | gokuls/hBERTv1_new_pretrain_cola | 0 | 2 | transformers | 2023-05-31T10:49:20 | ---
language:
- en
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- matthews_correlation
- accuracy
model-index:
- name: hBERTv1_new_pretrain_cola
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE COLA
type: glue
config: cola
s... | 2,533 | [
[
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MJ03/distilbert-base-uncased-distilled-clinc | 2023-05-31T11:20:34.000Z | [
"transformers",
"pytorch",
"distilbert",
"text-classification",
"generated_from_trainer",
"dataset:clinc_oos",
"license:apache-2.0",
"model-index",
"endpoints_compatible",
"region:us"
] | text-classification | MJ03 | null | null | MJ03/distilbert-base-uncased-distilled-clinc | 0 | 2 | transformers | 2023-05-31T11:09:41 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- clinc_oos
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased-distilled-clinc
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: clinc_oos
type: clinc_oos
config: plus
... | 2,243 | [
[
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NickThe1/ppo-SnowballTargetTESTCOLAB | 2023-06-01T04:53:49.000Z | [
"ml-agents",
"tensorboard",
"onnx",
"SnowballTarget",
"deep-reinforcement-learning",
"reinforcement-learning",
"ML-Agents-SnowballTarget",
"region:us"
] | reinforcement-learning | NickThe1 | null | null | NickThe1/ppo-SnowballTargetTESTCOLAB | 0 | 2 | ml-agents | 2023-05-31T11:53:27 | ---
library_name: ml-agents
tags:
- SnowballTarget
- deep-reinforcement-learning
- reinforcement-learning
- ML-Agents-SnowballTarget
---
# **ppo** Agent playing **SnowballTarget**
This is a trained model of a **ppo** agent playing **SnowballTarget** using the [Unity ML-Agents Library](https://github.com/Unity-Tech... | 996 | [
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trung0209/autotrain-testrum3-63013135311 | 2023-05-31T12:54:50.000Z | [
"transformers",
"pytorch",
"safetensors",
"bert",
"text-classification",
"autotrain",
"unk",
"dataset:trung0209/autotrain-data-testrum3",
"co2_eq_emissions",
"endpoints_compatible",
"region:us"
] | text-classification | trung0209 | null | null | trung0209/autotrain-testrum3-63013135311 | 0 | 2 | transformers | 2023-05-31T12:53:08 | ---
tags:
- autotrain
- text-classification
language:
- unk
widget:
- text: "I love AutoTrain"
datasets:
- trung0209/autotrain-data-testrum3
co2_eq_emissions:
emissions: 0.18211514635496343
---
# Model Trained Using AutoTrain
- Problem type: Multi-class Classification
- Model ID: 63013135311
- CO2 Emissions (in gra... | 1,284 | [
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mlsyedrz/bart-prompt-generator | 2023-05-31T13:05:16.000Z | [
"transformers",
"tf",
"bart",
"text2text-generation",
"generated_from_keras_callback",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | text2text-generation | mlsyedrz | null | null | mlsyedrz/bart-prompt-generator | 0 | 2 | transformers | 2023-05-31T12:58:50 | ---
license: apache-2.0
tags:
- generated_from_keras_callback
model-index:
- name: bart-prompt-generator
results: []
---
<!-- 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. -->
# bart-prompt-... | 1,466 | [
[
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-0.... |
poltextlab/xlm-roberta-large-danish-legal-cap | 2023-07-04T17:40:32.000Z | [
"transformers",
"pytorch",
"xlm-roberta",
"text-classification",
"zero-shot-classification",
"da",
"license:mit",
"endpoints_compatible",
"region:us"
] | text-classification | poltextlab | null | null | poltextlab/xlm-roberta-large-danish-legal-cap | 0 | 2 | transformers | 2023-05-31T13:56:31 |
---
---
license: mit
language:
- da
tags:
- zero-shot-classification
- text-classification
- pytorch
metrics:
- accuracy
- f1-score
---
# xlm-roberta-large-danish-legal-cap
## Model description
An `xlm-roberta-large` model finetuned on danish training data containing texts of the `legal` domain labelled with [major to... | 5,615 | [
[
-0.040374755859375,
-0.0462646484375,
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0.0258331298828125,
-0.03228759765625,
-0.049896240234375,
-0.057098388671875,
... |
poltextlab/xlm-roberta-large-german-media-cap | 2023-07-04T17:40:31.000Z | [
"transformers",
"pytorch",
"xlm-roberta",
"text-classification",
"zero-shot-classification",
"de",
"license:mit",
"endpoints_compatible",
"region:us"
] | text-classification | poltextlab | null | null | poltextlab/xlm-roberta-large-german-media-cap | 1 | 2 | transformers | 2023-05-31T14:17:59 |
---
---
license: mit
language:
- de
tags:
- zero-shot-classification
- text-classification
- pytorch
metrics:
- accuracy
- f1-score
---
# xlm-roberta-large-german-media-cap
## Model description
An `xlm-roberta-large` model finetuned on german training data containing texts of the `media` domain labelled with [major to... | 5,613 | [
[
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0.01282501220703125,
0.0177154541015625,
-0.04046630859375,
-0.046234130859375,
-0.05743408203125... |
PFcoding/medicare-gpt2-accurate | 2023-05-31T14:30:34.000Z | [
"transformers",
"pytorch",
"tensorboard",
"gpt2",
"text-generation",
"generated_from_trainer",
"dataset:pubmed-summarization",
"license:mit",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | text-generation | PFcoding | null | null | PFcoding/medicare-gpt2-accurate | 0 | 2 | transformers | 2023-05-31T14:24:24 | ---
license: mit
tags:
- generated_from_trainer
datasets:
- pubmed-summarization
model-index:
- name: medicare-gpt2-accurate
results: []
---
<!-- 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 co... | 1,192 | [
[
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-0.0281829833984375,
-0.0572509765625,
-0.0032... |
PFcoding/medicare-gpt2-large | 2023-07-31T02:10:02.000Z | [
"transformers",
"pytorch",
"tensorboard",
"gpt2",
"text-generation",
"generated_from_trainer",
"dataset:pubmed-summarization",
"license:mit",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | text-generation | PFcoding | null | null | PFcoding/medicare-gpt2-large | 1 | 2 | transformers | 2023-05-31T14:44:48 | ---
license: mit
tags:
- generated_from_trainer
datasets:
- pubmed-summarization
model-index:
- name: medicare-gpt2-large
results: []
---
<!-- 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 comme... | 2,017 | [
[
-0.021881103515625,
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0.0260009765625,
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... |
poltextlab/xlm-roberta-large-hungarian-other-cap | 2023-07-04T17:40:35.000Z | [
"transformers",
"pytorch",
"xlm-roberta",
"text-classification",
"zero-shot-classification",
"hu",
"license:mit",
"endpoints_compatible",
"region:us"
] | text-classification | poltextlab | null | null | poltextlab/xlm-roberta-large-hungarian-other-cap | 0 | 2 | transformers | 2023-05-31T14:44:52 |
---
---
license: mit
language:
- hu
tags:
- zero-shot-classification
- text-classification
- pytorch
metrics:
- accuracy
- f1-score
---
# xlm-roberta-large-hungarian-other-cap
## Model description
An `xlm-roberta-large` model finetuned on hungarian training data containing texts of the `other` domain labelled with [ma... | 5,559 | [
[
-0.041412353515625,
-0.0484619140625,
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0.0120697021484375,
0.0226287841796875,
-0.038848876953125,
-0.049102783203125,
-0.057464599609375,
... |
YakovElm/Apache10Classic_Balance_DATA_ratio_2 | 2023-05-31T15:05:54.000Z | [
"transformers",
"tf",
"bert",
"text-classification",
"generated_from_keras_callback",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | text-classification | YakovElm | null | null | YakovElm/Apache10Classic_Balance_DATA_ratio_2 | 0 | 2 | transformers | 2023-05-31T14:49:39 | ---
license: apache-2.0
tags:
- generated_from_keras_callback
model-index:
- name: Apache10Classic_Balance_DATA_ratio_2
results: []
---
<!-- 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. -->
... | 1,816 | [
[
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-0.024200... |
poltextlab/xlm-roberta-large-dutch-media-cap | 2023-07-04T17:40:36.000Z | [
"transformers",
"pytorch",
"xlm-roberta",
"text-classification",
"zero-shot-classification",
"nl",
"license:mit",
"endpoints_compatible",
"region:us"
] | text-classification | poltextlab | null | null | poltextlab/xlm-roberta-large-dutch-media-cap | 0 | 2 | transformers | 2023-05-31T14:53:24 |
---
---
license: mit
language:
- nl
tags:
- zero-shot-classification
- text-classification
- pytorch
metrics:
- accuracy
- f1-score
---
# xlm-roberta-large-dutch-media-cap
## Model description
An `xlm-roberta-large` model finetuned on dutch training data containing texts of the `media` domain labelled with [major topi... | 5,611 | [
[
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0.02117919921875,
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-0.046875,
-0.05853271484375,
0.008995056... |
poltextlab/xlm-roberta-large-hungarian-budget-cap | 2023-07-04T17:40:34.000Z | [
"transformers",
"pytorch",
"xlm-roberta",
"text-classification",
"zero-shot-classification",
"hu",
"license:mit",
"endpoints_compatible",
"region:us"
] | text-classification | poltextlab | null | null | poltextlab/xlm-roberta-large-hungarian-budget-cap | 0 | 2 | transformers | 2023-05-31T15:00:05 |
---
---
license: mit
language:
- hu
tags:
- zero-shot-classification
- text-classification
- pytorch
metrics:
- accuracy
- f1-score
---
# xlm-roberta-large-hungarian-budget-cap
## Model description
An `xlm-roberta-large` model finetuned on hungarian training data containing texts of the `budget` domain labelled with [... | 5,699 | [
[
-0.0440673828125,
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0.01427459716796875,
0.0218658447265625,
-0.040313720703125,
-0.045928955078125,
-0.053314208984375,
... |
YakovElm/Apache10Classic_Balance_DATA_ratio_3 | 2023-05-31T15:32:10.000Z | [
"transformers",
"tf",
"bert",
"text-classification",
"generated_from_keras_callback",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | text-classification | YakovElm | null | null | YakovElm/Apache10Classic_Balance_DATA_ratio_3 | 0 | 2 | transformers | 2023-05-31T15:07:35 | ---
license: apache-2.0
tags:
- generated_from_keras_callback
model-index:
- name: Apache10Classic_Balance_DATA_ratio_3
results: []
---
<!-- 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. -->
... | 1,816 | [
[
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0.0146484375,
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poltextlab/xlm-roberta-large-dutch-social-cap | 2023-07-04T17:40:33.000Z | [
"transformers",
"pytorch",
"xlm-roberta",
"text-classification",
"zero-shot-classification",
"nl",
"license:mit",
"endpoints_compatible",
"region:us"
] | text-classification | poltextlab | null | null | poltextlab/xlm-roberta-large-dutch-social-cap | 0 | 2 | transformers | 2023-05-31T15:20:13 |
---
---
license: mit
language:
- nl
tags:
- zero-shot-classification
- text-classification
- pytorch
metrics:
- accuracy
- f1-score
---
# xlm-roberta-large-dutch-social-cap
## Model description
An `xlm-roberta-large` model finetuned on dutch training data containing texts of the `social` domain labelled with [major to... | 5,615 | [
[
-0.04058837890625,
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0.0201416015625,
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poltextlab/xlm-roberta-large-italian-speech-cap | 2023-07-04T17:40:30.000Z | [
"transformers",
"pytorch",
"xlm-roberta",
"text-classification",
"zero-shot-classification",
"it",
"license:mit",
"endpoints_compatible",
"region:us"
] | text-classification | poltextlab | null | null | poltextlab/xlm-roberta-large-italian-speech-cap | 0 | 2 | transformers | 2023-05-31T15:26:52 |
---
---
license: mit
language:
- it
tags:
- zero-shot-classification
- text-classification
- pytorch
metrics:
- accuracy
- f1-score
---
# xlm-roberta-large-italian-speech-cap
## Model description
An `xlm-roberta-large` model finetuned on italian training data containing texts of the `speech` domain labelled with [majo... | 5,622 | [
[
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0.01306915283203125,
0.018310546875,
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-0.04852294921875,
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YakovElm/Apache10Classic_Balance_DATA_ratio_4 | 2023-05-31T16:03:37.000Z | [
"transformers",
"tf",
"bert",
"text-classification",
"generated_from_keras_callback",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | text-classification | YakovElm | null | null | YakovElm/Apache10Classic_Balance_DATA_ratio_4 | 0 | 2 | transformers | 2023-05-31T15:29:28 | ---
license: apache-2.0
tags:
- generated_from_keras_callback
model-index:
- name: Apache10Classic_Balance_DATA_ratio_4
results: []
---
<!-- 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. -->
... | 1,816 | [
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5IN/distilbert-base-uncased-finetuned-cola | 2023-06-10T15:05:17.000Z | [
"transformers",
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"generated_from_trainer",
"dataset:glue",
"license:apache-2.0",
"model-index",
"endpoints_compatible",
"region:us"
] | text-classification | 5IN | null | null | 5IN/distilbert-base-uncased-finetuned-cola | 0 | 2 | transformers | 2023-05-31T15:33:51 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- matthews_correlation
model-index:
- name: distilbert-base-uncased-finetuned-cola
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: glue
type: glue
config: cola
... | 2,042 | [
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-0.06304931640625,
-0.0... |
YakovElm/Apache15Classic_Balance_DATA_ratio_Half | 2023-05-31T16:12:30.000Z | [
"transformers",
"tf",
"bert",
"text-classification",
"generated_from_keras_callback",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | text-classification | YakovElm | null | null | YakovElm/Apache15Classic_Balance_DATA_ratio_Half | 0 | 2 | transformers | 2023-05-31T15:36:02 | ---
license: apache-2.0
tags:
- generated_from_keras_callback
model-index:
- name: Apache15Classic_Balance_DATA_ratio_Half
results: []
---
<!-- 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. -... | 1,822 | [
[
-0.044769287109375,
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0.00936126708984375,
0.01129150390625,
-0.031524658203125,
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0.0164642333984375,
0.01157379150390625,
-0.0567626953125,
-0.038543701171875,
-0.049896240234375,
... |
YakovElm/Apache15Classic_Balance_DATA_ratio_1 | 2023-05-31T16:23:55.000Z | [
"transformers",
"tf",
"bert",
"text-classification",
"generated_from_keras_callback",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | text-classification | YakovElm | null | null | YakovElm/Apache15Classic_Balance_DATA_ratio_1 | 0 | 2 | transformers | 2023-05-31T15:43:57 | ---
license: apache-2.0
tags:
- generated_from_keras_callback
model-index:
- name: Apache15Classic_Balance_DATA_ratio_1
results: []
---
<!-- 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. -->
... | 1,816 | [
[
-0.04608154296875,
-0.045867919921875,
0.01122283935546875,
0.01206207275390625,
-0.030303955078125,
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poltextlab/xlm-roberta-large-spanish-media-cap | 2023-07-04T17:40:30.000Z | [
"transformers",
"pytorch",
"xlm-roberta",
"text-classification",
"zero-shot-classification",
"es",
"license:mit",
"endpoints_compatible",
"region:us"
] | text-classification | poltextlab | null | null | poltextlab/xlm-roberta-large-spanish-media-cap | 0 | 2 | transformers | 2023-05-31T15:48:05 |
---
---
license: mit
language:
- es
tags:
- zero-shot-classification
- text-classification
- pytorch
metrics:
- accuracy
- f1-score
---
# xlm-roberta-large-spanish-media-cap
## Model description
An `xlm-roberta-large` model finetuned on spanish training data containing texts of the `media` domain labelled with [major ... | 5,619 | [
[
-0.042755126953125,
-0.047332763671875,
0.004573822021484375,
0.02490234375,
-0.003444671630859375,
-0.0010461807250976562,
-0.025634765625,
-0.022003173828125,
0.016845703125,
0.0203094482421875,
-0.03912353515625,
-0.047454833984375,
-0.056182861328125,
0.... |
poltextlab/xlm-roberta-large-italian-legal-cap | 2023-07-04T17:40:33.000Z | [
"transformers",
"pytorch",
"xlm-roberta",
"text-classification",
"zero-shot-classification",
"it",
"license:mit",
"endpoints_compatible",
"region:us"
] | text-classification | poltextlab | null | null | poltextlab/xlm-roberta-large-italian-legal-cap | 0 | 2 | transformers | 2023-05-31T15:54:53 |
---
---
license: mit
language:
- it
tags:
- zero-shot-classification
- text-classification
- pytorch
metrics:
- accuracy
- f1-score
---
# xlm-roberta-large-italian-legal-cap
## Model description
An `xlm-roberta-large` model finetuned on italian training data containing texts of the `legal` domain labelled with [major ... | 5,618 | [
[
-0.038726806640625,
-0.0460205078125,
0.008544921875,
0.0177459716796875,
-0.0075225830078125,
-0.0045928955078125,
-0.023529052734375,
-0.0263671875,
0.01485443115234375,
0.0227203369140625,
-0.03472900390625,
-0.04937744140625,
-0.05584716796875,
0.0090408... |
YakovElm/Apache15Classic_Balance_DATA_ratio_2 | 2023-05-31T16:40:38.000Z | [
"transformers",
"tf",
"bert",
"text-classification",
"generated_from_keras_callback",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | text-classification | YakovElm | null | null | YakovElm/Apache15Classic_Balance_DATA_ratio_2 | 0 | 2 | transformers | 2023-05-31T15:55:14 | ---
license: apache-2.0
tags:
- generated_from_keras_callback
model-index:
- name: Apache15Classic_Balance_DATA_ratio_2
results: []
---
<!-- 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. -->
... | 1,816 | [
[
-0.043670654296875,
-0.0457763671875,
0.011016845703125,
0.01220703125,
-0.032196044921875,
-0.031890869140625,
-0.01139068603515625,
-0.024566650390625,
0.0142364501953125,
0.012603759765625,
-0.054412841796875,
-0.035919189453125,
-0.050048828125,
-0.02630... |
poltextlab/xlm-roberta-large-dutch-manifesto-cap | 2023-07-04T17:40:35.000Z | [
"transformers",
"pytorch",
"xlm-roberta",
"text-classification",
"zero-shot-classification",
"nl",
"license:mit",
"endpoints_compatible",
"region:us"
] | text-classification | poltextlab | null | null | poltextlab/xlm-roberta-large-dutch-manifesto-cap | 0 | 2 | transformers | 2023-05-31T16:01:37 |
---
---
license: mit
language:
- nl
tags:
- zero-shot-classification
- text-classification
- pytorch
metrics:
- accuracy
- f1-score
---
# xlm-roberta-large-dutch-manifesto-cap
## Model description
An `xlm-roberta-large` model finetuned on dutch training data containing texts of the `manifesto` domain labelled with [ma... | 5,626 | [
[
-0.04168701171875,
-0.045074462890625,
0.005130767822265625,
0.022003173828125,
-0.003376007080078125,
-0.0024204254150390625,
-0.0258636474609375,
-0.026763916015625,
0.0156707763671875,
0.0217742919921875,
-0.037811279296875,
-0.04931640625,
-0.055908203125,
... |
YakovElm/Apache15Classic_Balance_DATA_ratio_3 | 2023-05-31T17:01:35.000Z | [
"transformers",
"tf",
"bert",
"text-classification",
"generated_from_keras_callback",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | text-classification | YakovElm | null | null | YakovElm/Apache15Classic_Balance_DATA_ratio_3 | 0 | 2 | transformers | 2023-05-31T16:09:56 | ---
license: apache-2.0
tags:
- generated_from_keras_callback
model-index:
- name: Apache15Classic_Balance_DATA_ratio_3
results: []
---
<!-- 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. -->
... | 1,816 | [
[
-0.045135498046875,
-0.045928955078125,
0.01389312744140625,
0.01216888427734375,
-0.0312042236328125,
-0.033050537109375,
-0.011138916015625,
-0.025360107421875,
0.013641357421875,
0.0146331787109375,
-0.053253173828125,
-0.03955078125,
-0.047943115234375,
... |
yoshivo/distilbert-base-uncased-finetuned-emotion | 2023-05-31T16:41:10.000Z | [
"transformers",
"pytorch",
"distilbert",
"text-classification",
"generated_from_trainer",
"dataset:emotion",
"license:apache-2.0",
"model-index",
"endpoints_compatible",
"region:us"
] | text-classification | yoshivo | null | null | yoshivo/distilbert-base-uncased-finetuned-emotion | 0 | 2 | transformers | 2023-05-31T16:21:48 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- emotion
metrics:
- accuracy
- f1
model-index:
- name: distilbert-base-uncased-finetuned-emotion
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: emotion
type: emotion
config: split... | 1,851 | [
[
-0.03839111328125,
-0.04034423828125,
0.0140228271484375,
0.02386474609375,
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0.01107025146484375,
0.00887298583984375,
-0.057464599609375,
-0.052276611328125,
-0.060791015625,
... |
YakovElm/Apache15Classic_Balance_DATA_ratio_4 | 2023-05-31T17:26:47.000Z | [
"transformers",
"tf",
"bert",
"text-classification",
"generated_from_keras_callback",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | text-classification | YakovElm | null | null | YakovElm/Apache15Classic_Balance_DATA_ratio_4 | 0 | 2 | transformers | 2023-05-31T16:27:20 | ---
license: apache-2.0
tags:
- generated_from_keras_callback
model-index:
- name: Apache15Classic_Balance_DATA_ratio_4
results: []
---
<!-- 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. -->
... | 1,816 | [
[
-0.045257568359375,
-0.04461669921875,
0.01422119140625,
0.0122528076171875,
-0.0309600830078125,
-0.030731201171875,
-0.01190185546875,
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0.0142059326171875,
0.01336669921875,
-0.0543212890625,
-0.039581298828125,
-0.048614501953125,
-0.0... |
YakovElm/Apache20Classic_Balance_DATA_ratio_Half | 2023-05-31T17:34:48.000Z | [
"transformers",
"tf",
"bert",
"text-classification",
"generated_from_keras_callback",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | text-classification | YakovElm | null | null | YakovElm/Apache20Classic_Balance_DATA_ratio_Half | 0 | 2 | transformers | 2023-05-31T16:32:53 | ---
license: apache-2.0
tags:
- generated_from_keras_callback
model-index:
- name: Apache20Classic_Balance_DATA_ratio_Half
results: []
---
<!-- 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. -... | 1,822 | [
[
-0.045379638671875,
-0.047332763671875,
0.0112152099609375,
0.01422882080078125,
-0.0323486328125,
-0.031036376953125,
-0.007320404052734375,
-0.0248260498046875,
0.0172576904296875,
0.0132904052734375,
-0.058563232421875,
-0.038818359375,
-0.05072021484375,
... |
poltextlab/xlm-roberta-large-dutch-speech-cap | 2023-07-04T17:40:34.000Z | [
"transformers",
"pytorch",
"xlm-roberta",
"text-classification",
"zero-shot-classification",
"nl",
"license:mit",
"endpoints_compatible",
"region:us"
] | text-classification | poltextlab | null | null | poltextlab/xlm-roberta-large-dutch-speech-cap | 0 | 2 | transformers | 2023-05-31T16:37:38 |
---
---
license: mit
language:
- nl
tags:
- zero-shot-classification
- text-classification
- pytorch
metrics:
- accuracy
- f1-score
---
# xlm-roberta-large-dutch-speech-cap
## Model description
An `xlm-roberta-large` model finetuned on dutch training data containing texts of the `speech` domain labelled with [major to... | 5,614 | [
[
-0.042083740234375,
-0.052215576171875,
0.003490447998046875,
0.0234832763671875,
-0.00426483154296875,
-0.00395965576171875,
-0.0301971435546875,
-0.0254974365234375,
0.01433563232421875,
0.022430419921875,
-0.03558349609375,
-0.049041748046875,
-0.056274414062... |
YakovElm/Apache20Classic_Balance_DATA_ratio_1 | 2023-05-31T17:44:28.000Z | [
"transformers",
"tf",
"bert",
"text-classification",
"generated_from_keras_callback",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | text-classification | YakovElm | null | null | YakovElm/Apache20Classic_Balance_DATA_ratio_1 | 0 | 2 | transformers | 2023-05-31T16:39:27 | ---
license: apache-2.0
tags:
- generated_from_keras_callback
model-index:
- name: Apache20Classic_Balance_DATA_ratio_1
results: []
---
<!-- 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. -->
... | 1,816 | [
[
-0.046661376953125,
-0.0472412109375,
0.01198577880859375,
0.0133209228515625,
-0.03155517578125,
-0.033966064453125,
-0.0105133056640625,
-0.024688720703125,
0.0155029296875,
0.0146331787109375,
-0.056060791015625,
-0.038421630859375,
-0.050079345703125,
-0... |
poltextlab/xlm-roberta-large-dutch-legal-cap | 2023-07-04T17:40:38.000Z | [
"transformers",
"pytorch",
"xlm-roberta",
"text-classification",
"zero-shot-classification",
"nl",
"license:mit",
"endpoints_compatible",
"region:us"
] | text-classification | poltextlab | null | null | poltextlab/xlm-roberta-large-dutch-legal-cap | 1 | 2 | transformers | 2023-05-31T16:44:36 |
---
---
license: mit
language:
- nl
tags:
- zero-shot-classification
- text-classification
- pytorch
metrics:
- accuracy
- f1-score
---
# xlm-roberta-large-dutch-legal-cap
## Model description
An `xlm-roberta-large` model finetuned on dutch training data containing texts of the `legal` domain labelled with [major topi... | 5,611 | [
[
-0.039520263671875,
-0.047271728515625,
0.00728607177734375,
0.0208587646484375,
-0.007205963134765625,
-0.005153656005859375,
-0.0245361328125,
-0.0266265869140625,
0.01416015625,
0.0257568359375,
-0.03228759765625,
-0.0496826171875,
-0.05816650390625,
0.00... |
YakovElm/Apache20Classic_Balance_DATA_ratio_2 | 2023-05-31T17:57:33.000Z | [
"transformers",
"tf",
"bert",
"text-classification",
"generated_from_keras_callback",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | text-classification | YakovElm | null | null | YakovElm/Apache20Classic_Balance_DATA_ratio_2 | 0 | 2 | transformers | 2023-05-31T16:48:23 | ---
license: apache-2.0
tags:
- generated_from_keras_callback
model-index:
- name: Apache20Classic_Balance_DATA_ratio_2
results: []
---
<!-- 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. -->
... | 1,816 | [
[
-0.044158935546875,
-0.04693603515625,
0.0119476318359375,
0.0140838623046875,
-0.032440185546875,
-0.033294677734375,
-0.01078033447265625,
-0.0261993408203125,
0.0139007568359375,
0.01409912109375,
-0.055419921875,
-0.036224365234375,
-0.050567626953125,
-... |
poltextlab/xlm-roberta-large-spanish-other-cap | 2023-07-04T17:40:39.000Z | [
"transformers",
"pytorch",
"xlm-roberta",
"text-classification",
"zero-shot-classification",
"es",
"license:mit",
"endpoints_compatible",
"region:us"
] | text-classification | poltextlab | null | null | poltextlab/xlm-roberta-large-spanish-other-cap | 0 | 2 | transformers | 2023-05-31T16:51:21 |
---
---
license: mit
language:
- es
tags:
- zero-shot-classification
- text-classification
- pytorch
metrics:
- accuracy
- f1-score
---
# xlm-roberta-large-spanish-other-cap
## Model description
An `xlm-roberta-large` model finetuned on spanish training data containing texts of the `other` domain labelled with [major ... | 5,618 | [
[
-0.041015625,
-0.048797607421875,
0.00658416748046875,
0.025177001953125,
-0.00443267822265625,
-0.0009899139404296875,
-0.0270538330078125,
-0.02813720703125,
0.0164337158203125,
0.0222015380859375,
-0.03790283203125,
-0.048431396484375,
-0.057098388671875,
... |
YakovElm/Apache20Classic_Balance_DATA_ratio_3 | 2023-05-31T18:14:15.000Z | [
"transformers",
"tf",
"bert",
"text-classification",
"generated_from_keras_callback",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | text-classification | YakovElm | null | null | YakovElm/Apache20Classic_Balance_DATA_ratio_3 | 0 | 2 | transformers | 2023-05-31T17:05:13 | ---
license: apache-2.0
tags:
- generated_from_keras_callback
model-index:
- name: Apache20Classic_Balance_DATA_ratio_3
results: []
---
<!-- 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. -->
... | 1,816 | [
[
-0.0458984375,
-0.046966552734375,
0.01491546630859375,
0.01470184326171875,
-0.032318115234375,
-0.034698486328125,
-0.01055145263671875,
-0.0264892578125,
0.01375579833984375,
0.01568603515625,
-0.054229736328125,
-0.0390625,
-0.049163818359375,
-0.0230865... |
Ibrahim-Alam/finetuning-xlm-mlm-en-2048-on-sst2 | 2023-05-31T18:27:27.000Z | [
"transformers",
"pytorch",
"tensorboard",
"xlm",
"text-classification",
"generated_from_trainer",
"dataset:sst2",
"license:cc-by-nc-4.0",
"model-index",
"endpoints_compatible",
"region:us"
] | text-classification | Ibrahim-Alam | null | null | Ibrahim-Alam/finetuning-xlm-mlm-en-2048-on-sst2 | 0 | 2 | transformers | 2023-05-31T17:24:55 | ---
license: cc-by-nc-4.0
tags:
- generated_from_trainer
datasets:
- sst2
metrics:
- accuracy
- f1
model-index:
- name: finetuning-xlm-mlm-en-2048-on-sst2
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: sst2
type: sst2
config: default
split... | 1,540 | [
[
-0.01479339599609375,
-0.042388916015625,
0.018402099609375,
0.013031005859375,
-0.032623291015625,
-0.0239105224609375,
-0.013671875,
-0.0164337158203125,
0.0005583763122558594,
0.0389404296875,
-0.0577392578125,
-0.04119873046875,
-0.049713134765625,
-0.00... |
poltextlab/xlm-roberta-large-hungarian-media-cap | 2023-07-04T17:40:39.000Z | [
"transformers",
"pytorch",
"xlm-roberta",
"text-classification",
"zero-shot-classification",
"hu",
"license:mit",
"endpoints_compatible",
"region:us"
] | text-classification | poltextlab | null | null | poltextlab/xlm-roberta-large-hungarian-media-cap | 0 | 2 | transformers | 2023-05-31T17:25:14 |
---
---
license: mit
language:
- hu
tags:
- zero-shot-classification
- text-classification
- pytorch
metrics:
- accuracy
- f1-score
---
# xlm-roberta-large-hungarian-media-cap
## Model description
An `xlm-roberta-large` model finetuned on hungarian training data containing texts of the `media` domain labelled with [ma... | 5,694 | [
[
-0.042633056640625,
-0.048126220703125,
0.00534820556640625,
0.019622802734375,
-0.0043487548828125,
-0.003437042236328125,
-0.026519775390625,
-0.0217132568359375,
0.01457977294921875,
0.019561767578125,
-0.040252685546875,
-0.048431396484375,
-0.05670166015625... |
YakovElm/Apache20Classic_Balance_DATA_ratio_4 | 2023-05-31T18:34:20.000Z | [
"transformers",
"tf",
"bert",
"text-classification",
"generated_from_keras_callback",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | text-classification | YakovElm | null | null | YakovElm/Apache20Classic_Balance_DATA_ratio_4 | 0 | 2 | transformers | 2023-05-31T17:26:33 | ---
license: apache-2.0
tags:
- generated_from_keras_callback
model-index:
- name: Apache20Classic_Balance_DATA_ratio_4
results: []
---
<!-- 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. -->
... | 1,816 | [
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poltextlab/xlm-roberta-large-english-media-cap | 2023-07-04T17:40:29.000Z | [
"transformers",
"pytorch",
"xlm-roberta",
"text-classification",
"zero-shot-classification",
"en",
"license:mit",
"endpoints_compatible",
"region:us"
] | text-classification | poltextlab | null | null | poltextlab/xlm-roberta-large-english-media-cap | 0 | 2 | transformers | 2023-05-31T17:31:55 |
---
---
license: mit
language:
- en
tags:
- zero-shot-classification
- text-classification
- pytorch
metrics:
- accuracy
- f1-score
---
# xlm-roberta-large-english-media-cap
## Model description
An `xlm-roberta-large` model finetuned on english training data containing texts of the `media` domain labelled with [major ... | 5,687 | [
[
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poltextlab/xlm-roberta-large-english-other-cap | 2023-07-04T17:40:39.000Z | [
"transformers",
"pytorch",
"xlm-roberta",
"text-classification",
"zero-shot-classification",
"en",
"license:mit",
"endpoints_compatible",
"region:us"
] | text-classification | poltextlab | null | null | poltextlab/xlm-roberta-large-english-other-cap | 0 | 2 | transformers | 2023-05-31T17:38:35 |
---
---
license: mit
language:
- en
tags:
- zero-shot-classification
- text-classification
- pytorch
metrics:
- accuracy
- f1-score
---
# xlm-roberta-large-english-other-cap
## Model description
An `xlm-roberta-large` model finetuned on english training data containing texts of the `other` domain labelled with [major ... | 5,686 | [
[
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0.0... |
Showroom/beauty_subcategory_classifier | 2023-05-31T17:44:37.000Z | [
"transformers",
"pytorch",
"safetensors",
"bert",
"text-classification",
"autotrain",
"en",
"dataset:Showroom/autotrain-data-beauty_categories",
"co2_eq_emissions",
"endpoints_compatible",
"region:us"
] | text-classification | Showroom | null | null | Showroom/beauty_subcategory_classifier | 1 | 2 | transformers | 2023-05-31T17:41:57 | ---
tags:
- autotrain
- text-classification
language:
- en
widget:
- text: "I love AutoTrain"
datasets:
- Showroom/autotrain-data-beauty_categories
co2_eq_emissions:
emissions: 0.4401601303255541
---
# Model Trained Using AutoTrain
- Problem type: Multi-class Classification
- Model ID: 63190135345
- CO2 Emissions (... | 1,314 | [
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guilhermelabigalini/distilbert-base-uncased-finetuned-emotion | 2023-05-31T21:07:26.000Z | [
"transformers",
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"generated_from_trainer",
"dataset:emotion",
"license:apache-2.0",
"model-index",
"endpoints_compatible",
"region:us"
] | text-classification | guilhermelabigalini | null | null | guilhermelabigalini/distilbert-base-uncased-finetuned-emotion | 0 | 2 | transformers | 2023-05-31T18:03:05 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- emotion
metrics:
- accuracy
- f1
model-index:
- name: distilbert-base-uncased-finetuned-emotion
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: emotion
type: emotion
config: split... | 1,845 | [
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sofia-todeschini/BioLinkBERT-LitCovid-v1.0 | 2023-06-15T17:44:27.000Z | [
"transformers",
"pytorch",
"bert",
"text-classification",
"license:mit",
"endpoints_compatible",
"region:us"
] | text-classification | sofia-todeschini | null | null | sofia-todeschini/BioLinkBERT-LitCovid-v1.0 | 0 | 2 | transformers | 2023-05-31T18:48:52 | ---
license: mit
---
# BioLinkBERT-LitCovid-v1.0
This model is a fine-tuned version of [michiyasunaga/BioLinkBERT-base](https://huggingface.co/michiyasunaga/BioLinkBERT-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1098
- F1: 0.8992
- Roc Auc: 0.9330
- Accuracy: 0.7945... | 1,146 | [
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Xenova/finbert | 2023-05-31T20:20:46.000Z | [
"transformers.js",
"onnx",
"bert",
"text-classification",
"region:us"
] | text-classification | Xenova | null | null | Xenova/finbert | 0 | 2 | transformers.js | 2023-05-31T20:20:06 | ---
library_name: "transformers.js"
---
https://huggingface.co/ProsusAI/finbert with ONNX weights to be compatible with Transformers.js.
Note: Having a separate repo for ONNX weights is intended to be a temporary solution until WebML gains more traction. If you would like to make your models web-ready, we recommend c... | 495 | [
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jfforero/a_different_name2 | 2023-05-31T20:22:27.000Z | [
"transformers",
"tf",
"bert",
"text-classification",
"generated_from_keras_callback",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | text-classification | jfforero | null | null | jfforero/a_different_name2 | 0 | 2 | transformers | 2023-05-31T20:22:00 | ---
license: apache-2.0
tags:
- generated_from_keras_callback
model-index:
- name: a_different_name2
results: []
---
<!-- 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. -->
# a_different_name... | 936 | [
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LazarusNLP/simcse-indobert-lite-base | 2023-05-31T20:57:21.000Z | [
"sentence-transformers",
"pytorch",
"albert",
"feature-extraction",
"sentence-similarity",
"transformers",
"dataset:LazarusNLP/wikipedia_id_20230520",
"endpoints_compatible",
"region:us"
] | sentence-similarity | LazarusNLP | null | null | LazarusNLP/simcse-indobert-lite-base | 0 | 2 | sentence-transformers | 2023-05-31T20:57:17 | ---
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- transformers
datasets:
- LazarusNLP/wikipedia_id_20230520
---
# LazarusNLP/simcse-indobert-lite-base
This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 768 ... | 4,116 | [
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0.02001953125,
0.020751953125,
-0.042633056640625,
-0.0458984375,
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0.00272178... |
jayanta/xlm-roberta-base-english-sentweet-derogatory | 2023-05-31T22:33:48.000Z | [
"transformers",
"pytorch",
"tensorboard",
"xlm-roberta",
"text-classification",
"generated_from_trainer",
"license:mit",
"endpoints_compatible",
"region:us"
] | text-classification | jayanta | null | null | jayanta/xlm-roberta-base-english-sentweet-derogatory | 0 | 2 | transformers | 2023-05-31T22:12:28 | ---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: xlm-roberta-base-english-sentweet-derogatory
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread a... | 1,997 | [
[
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-... |
dedgington/vit-small-ds | 2023-06-15T01:00:12.000Z | [
"keras",
"region:us"
] | null | dedgington | null | null | dedgington/vit-small-ds | 0 | 2 | keras | 2023-05-31T23:21:30 | ---
library_name: 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:
| Hyperparameters ... | 843 | [
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AG6019/distilbert-base-uncased-finetuned-sst2-ag | 2023-06-01T01:07:12.000Z | [
"transformers",
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"generated_from_trainer",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | text-classification | AG6019 | null | null | AG6019/distilbert-base-uncased-finetuned-sst2-ag | 0 | 2 | transformers | 2023-06-01T00:57:26 | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased-finetuned-sst2-ag
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then r... | 1,947 | [
[
-0.0269317626953125,
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... |
razerblade072611/EleutherAI2 | 2023-06-02T01:09:28.000Z | [
"transformers",
"pytorch",
"jax",
"rust",
"gpt_neo",
"text-generation",
"doi:10.57967/hf/0709",
"endpoints_compatible",
"region:us"
] | text-generation | razerblade072611 | null | null | razerblade072611/EleutherAI2 | 0 | 2 | transformers | 2023-06-01T01:26:42 | MAIN_SCRIPT_MODULE
(common_module)
import atexit
import nltk
import pyttsx3
import spacy
import speech_recognition as sr
import torch
from transformers import GPTNeoForCausalLM, AutoTokenizer
from nltk.sentiment import SentimentIntensityAnalyzer
import os
import json
from memory_module import MemoryModule
from sentim... | 10,675 | [
[
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-0.0406494140625,
-0.0360107421875,
-0.0... |
Shuddup/depression_classifier_2 | 2023-06-01T03:06:10.000Z | [
"transformers",
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"generated_from_trainer",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | text-classification | Shuddup | null | null | Shuddup/depression_classifier_2 | 0 | 2 | transformers | 2023-06-01T02:51:00 | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: depression_classifier_2
results: []
---
<!-- 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... | 1,415 | [
[
-0.029449462890625,
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-0.046905517578125,
-0.056610107421875,
-0.0690307617... |
Augustin99/distilbert-base-uncased-finetuned-cola | 2023-06-01T03:33:49.000Z | [
"transformers",
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"generated_from_trainer",
"dataset:glue",
"license:apache-2.0",
"model-index",
"endpoints_compatible",
"region:us"
] | text-classification | Augustin99 | null | null | Augustin99/distilbert-base-uncased-finetuned-cola | 0 | 2 | transformers | 2023-06-01T02:51:36 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- matthews_correlation
model-index:
- name: distilbert-base-uncased-finetuned-cola
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: glue
type: glue
config: cola
... | 2,042 | [
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exbow/TinyStories-wikitrain-33m-ethan | 2023-06-01T06:26:02.000Z | [
"transformers",
"pytorch",
"tensorboard",
"gpt_neo",
"text-generation",
"generated_from_trainer",
"endpoints_compatible",
"region:us"
] | text-generation | exbow | null | null | exbow/TinyStories-wikitrain-33m-ethan | 0 | 2 | transformers | 2023-06-01T03:19:18 | ---
tags:
- generated_from_trainer
model-index:
- name: TinyStories-wikitrain-33m-ethan
results: []
---
<!-- 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. -->
# TinyStories-wikitrain-3... | 1,385 | [
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wesleyacheng/twitter-emotion-classification-with-bert | 2023-06-08T00:04:58.000Z | [
"transformers",
"pytorch",
"safetensors",
"distilbert",
"text-classification",
"en",
"dataset:tweet_eval",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | text-classification | wesleyacheng | null | null | wesleyacheng/twitter-emotion-classification-with-bert | 0 | 2 | transformers | 2023-06-01T03:27:25 | ---
license: apache-2.0
datasets:
- tweet_eval
language:
- en
metrics:
- accuracy
- f1
pipeline_tag: text-classification
widget:
- text: Yay!
example_title: Joy Example
- text: There is no meaning in life.
example_title: Sadness Example
- text: I hate you!
example_title: Anger Example
---
First poste... | 1,136 | [
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TigerResearch/tigerbot-7b-sft-v1-4bit | 2023-08-10T08:43:46.000Z | [
"transformers",
"bloom",
"text-generation",
"license:apache-2.0",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | text-generation | TigerResearch | null | null | TigerResearch/tigerbot-7b-sft-v1-4bit | 6 | 2 | transformers | 2023-06-01T03:38:20 | ---
license: apache-2.0
---
<div style="width: 100%;">
<img src="https://github.com/TigerResearch/TigerBot/blob/main/image/logo_core.png" alt="TigerBot" style="width: 20%; display: block; margin: auto;">
</div>
<p align="center">
<font face="黑体" size=5"> A cutting-edge foundation for your very own LLM. </font>
</p>... | 1,349 | [
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0.000774383544... |
jojoUla/bert-large-cased-sigir-support-refute-no-label-40-2nd-test-LR10-8-fast-21 | 2023-06-01T07:18:54.000Z | [
"transformers",
"pytorch",
"tensorboard",
"bert",
"fill-mask",
"generated_from_trainer",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | fill-mask | jojoUla | null | null | jojoUla/bert-large-cased-sigir-support-refute-no-label-40-2nd-test-LR10-8-fast-21 | 0 | 2 | transformers | 2023-06-01T04:17:08 | ---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: bert-large-cased-sigir-support-refute-no-label-40-2nd-test-LR10-8-fast-21
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complet... | 1,807 | [
[
-0.04150390625,
-0.04071044921875,
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0.0281219482421875,
-0.05133056640625,
-0.037811279296875,
-0.05401611328125,
-0.0119... |
vagrawal787/trip-review-test-2 | 2023-06-01T05:14:40.000Z | [
"transformers",
"pytorch",
"tensorboard",
"bert",
"text-classification",
"generated_from_trainer",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | text-classification | vagrawal787 | null | null | vagrawal787/trip-review-test-2 | 0 | 2 | transformers | 2023-06-01T04:58:16 | ---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: trip-review-test-2
results: []
---
<!-- 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. -->
# trip-review-test... | 1,027 | [
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Retrial9842/dqn-SpaceInvadersNoFrameskip-v4 | 2023-06-01T05:47:13.000Z | [
"stable-baselines3",
"SpaceInvadersNoFrameskip-v4",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | reinforcement-learning | Retrial9842 | null | null | Retrial9842/dqn-SpaceInvadersNoFrameskip-v4 | 0 | 2 | stable-baselines3 | 2023-06-01T05:46:35 | ---
library_name: stable-baselines3
tags:
- SpaceInvadersNoFrameskip-v4
- deep-reinforcement-learning
- reinforcement-learning
- stable-baselines3
model-index:
- name: DQN
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: SpaceInvadersNoFrameskip-v4
... | 2,768 | [
[
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-0.034515380859375,
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-0... |
SHENMU007/neunit_BASE_V7 | 2023-06-05T06:35:07.000Z | [
"transformers",
"pytorch",
"tensorboard",
"speecht5",
"text-to-audio",
"1.1.0",
"generated_from_trainer",
"zh",
"dataset:facebook/voxpopuli",
"license:mit",
"endpoints_compatible",
"region:us"
] | text-to-audio | SHENMU007 | null | null | SHENMU007/neunit_BASE_V7 | 0 | 2 | transformers | 2023-06-01T06:11:29 | ---
language:
- zh
license: mit
tags:
- 1.1.0
- generated_from_trainer
datasets:
- facebook/voxpopuli
model-index:
- name: SpeechT5 TTS Dutch neunit
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete... | 1,246 | [
[
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-0.05059814453125,
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0.... |
notaphoenix/shakespeare_classifier_model | 2023-09-27T12:00:41.000Z | [
"transformers",
"pytorch",
"safetensors",
"distilbert",
"text-classification",
"en",
"dataset:notaphoenix/shakespeare_dataset",
"license:mit",
"endpoints_compatible",
"region:us"
] | text-classification | notaphoenix | null | null | notaphoenix/shakespeare_classifier_model | 0 | 2 | transformers | 2023-06-01T06:41:40 | ---
license: mit
datasets:
- notaphoenix/shakespeare_dataset
language:
- en
metrics:
- f1
pipeline_tag: text-classification
---
# Shakespeare/Modern English DistilBert-base
# Description ℹ
With this model, you can classify if an English sentence has a *Shakespearean* style or a *modern* style
The model is a fine-t... | 1,047 | [
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-0.069763183593... |
poltextlab/xlm-roberta-large-dutch-budget-cap | 2023-07-04T17:40:37.000Z | [
"transformers",
"pytorch",
"xlm-roberta",
"text-classification",
"zero-shot-classification",
"nl",
"license:mit",
"endpoints_compatible",
"region:us"
] | text-classification | poltextlab | null | null | poltextlab/xlm-roberta-large-dutch-budget-cap | 0 | 2 | transformers | 2023-06-01T06:53:14 |
---
---
license: mit
language:
- nl
tags:
- zero-shot-classification
- text-classification
- pytorch
metrics:
- accuracy
- f1-score
---
# xlm-roberta-large-dutch-budget-cap
## Model description
An `xlm-roberta-large` model finetuned on dutch training data containing texts of the `budget` domain labelled with [major to... | 5,547 | [
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seungkim1313/distilbert-base-uncased-finetuned-emotion | 2023-06-01T10:06:00.000Z | [
"transformers",
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"generated_from_trainer",
"dataset:emotion",
"license:apache-2.0",
"model-index",
"endpoints_compatible",
"region:us"
] | text-classification | seungkim1313 | null | null | seungkim1313/distilbert-base-uncased-finetuned-emotion | 0 | 2 | transformers | 2023-06-01T07:21:00 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- emotion
metrics:
- accuracy
- f1
model-index:
- name: distilbert-base-uncased-finetuned-emotion
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: emotion
type: emotion
config: split... | 1,848 | [
[
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jangmin/whisper-small-ko-normalized-debug | 2023-06-01T09:00:19.000Z | [
"transformers",
"pytorch",
"tensorboard",
"whisper",
"automatic-speech-recognition",
"generated_from_trainer",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | automatic-speech-recognition | jangmin | null | null | jangmin/whisper-small-ko-normalized-debug | 0 | 2 | transformers | 2023-06-01T08:35:29 | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-small-ko-normalized-debug
results: []
---
<!-- 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 co... | 1,546 | [
[
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emresvd/u160 | 2023-06-01T09:26:53.000Z | [
"keras",
"region:us"
] | null | emresvd | null | null | emresvd/u160 | 0 | 2 | keras | 2023-06-01T09:26:50 | ---
library_name: 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:
| Hyperparameters ... | 841 | [
[
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... |
jayanta/distilbert-base-uncased-english-sentweet-derogatory | 2023-06-01T20:09:37.000Z | [
"transformers",
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"generated_from_trainer",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | text-classification | jayanta | null | null | jayanta/distilbert-base-uncased-english-sentweet-derogatory | 0 | 2 | transformers | 2023-06-01T11:20:59 | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: distilbert-base-uncased-english-sentweet-derogatory
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probab... | 2,080 | [
[
-0.032623291015625,
-0.039459228515625,
0.007556915283203125,
0.0146484375,
-0.019775390625,
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0.01415252685546875,
-0.051300048828125,
-0.05340576171875,
-0.05328369140625,
-0.00844... |
golaxy/gogpt-math-560m | 2023-06-01T14:17:30.000Z | [
"transformers",
"pytorch",
"bloom",
"text-generation",
"zh",
"dataset:BelleGroup/train_2M_CN",
"dataset:BelleGroup/train_3.5M_CN",
"dataset:BelleGroup/train_1M_CN",
"dataset:BelleGroup/train_0.5M_CN",
"dataset:BelleGroup/school_math_0.25M",
"license:apache-2.0",
"endpoints_compatible",
"text... | text-generation | golaxy | null | null | golaxy/gogpt-math-560m | 0 | 2 | transformers | 2023-06-01T13:19:14 | ---
license: apache-2.0
datasets:
- BelleGroup/train_2M_CN
- BelleGroup/train_3.5M_CN
- BelleGroup/train_1M_CN
- BelleGroup/train_0.5M_CN
- BelleGroup/school_math_0.25M
language:
- zh
---
## GoGPT
基于中文指令数据微调BLOOM
> 训练第一轮足够了，后续第二轮和第三轮提升不大
- 🚀多样性指令数据
- 🚀筛选高质量中文数据
| 模型名字 | 参数量 ... | 1,139 | [
[
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Sandiago21/llama-13b-hf-prompt-answering | 2023-06-12T09:30:27.000Z | [
"transformers",
"pytorch",
"llama",
"text-generation",
"decapoda-research-13b-hf",
"prompt answering",
"peft",
"en",
"license:other",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | text-generation | Sandiago21 | null | null | Sandiago21/llama-13b-hf-prompt-answering | 1 | 2 | transformers | 2023-06-01T13:53:12 | ---
license: other
language:
- en
library_name: transformers
pipeline_tag: text-generation
tags:
- llama
- decapoda-research-13b-hf
- prompt answering
- peft
---
## Model Card for Model ID
This repository contains a LLaMA-13B further fine-tuned model on conversations and question answering prompts.
⚠️ **I used [LLaM... | 6,992 | [
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-0.035797119140625,
-0.038177490234375,
0.0115... |
Alexandra2398/deberta_amazon_reviews_v1 | 2023-06-01T18:03:55.000Z | [
"transformers",
"pytorch",
"tensorboard",
"deberta-v2",
"text-classification",
"generated_from_trainer",
"license:mit",
"endpoints_compatible",
"region:us"
] | text-classification | Alexandra2398 | null | null | Alexandra2398/deberta_amazon_reviews_v1 | 0 | 2 | transformers | 2023-06-01T14:38:52 | ---
license: mit
tags:
- generated_from_trainer
model-index:
- name: deberta_amazon_reviews_v1
results: []
---
<!-- 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. -->
# deberta_amazon_r... | 1,097 | [
[
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0xYuan/autotrain-b-63449135459 | 2023-06-01T14:50:08.000Z | [
"transformers",
"pytorch",
"safetensors",
"bert",
"text-classification",
"autotrain",
"zh",
"dataset:0xYuan/autotrain-data-b",
"co2_eq_emissions",
"endpoints_compatible",
"region:us"
] | text-classification | 0xYuan | null | null | 0xYuan/autotrain-b-63449135459 | 0 | 2 | transformers | 2023-06-01T14:42:45 | ---
tags:
- autotrain
- text-classification
language:
- zh
widget:
- text: "I love AutoTrain"
datasets:
- 0xYuan/autotrain-data-b
co2_eq_emissions:
emissions: 4.720376981365927
---
# Model Trained Using AutoTrain
- Problem type: Binary Classification
- Model ID: 63449135459
- CO2 Emissions (in grams): 4.7204
## Va... | 1,091 | [
[
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-0.0040435791015625,
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0.006591796875,
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0.0006470680236816406,
0.01009368896484375,
-0.054168701171875,
-0.036346435546875,
-0.0618591308593... |
peanutacake/autotrain-ann_nl-63427135534 | 2023-06-01T18:28:28.000Z | [
"transformers",
"pytorch",
"safetensors",
"bert",
"token-classification",
"autotrain",
"nl",
"dataset:peanutacake/autotrain-data-ann_nl",
"co2_eq_emissions",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | token-classification | peanutacake | null | null | peanutacake/autotrain-ann_nl-63427135534 | 0 | 2 | transformers | 2023-06-01T18:27:23 | ---
tags:
- autotrain
- token-classification
language:
- nl
widget:
- text: "I love AutoTrain"
datasets:
- peanutacake/autotrain-data-ann_nl
co2_eq_emissions:
emissions: 0.18640961989795524
---
# Model Trained Using AutoTrain
- Problem type: Entity Extraction
- Model ID: 63427135534
- CO2 Emissions (in grams): 0.18... | 1,111 | [
[
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0.007152557373046875,
0.014007568359375,
-0.049774169921875,
-0.03729248046875,
-0.0620727... |
AG6019/reddit-comment-sentiment-final | 2023-06-01T19:54:57.000Z | [
"transformers",
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"generated_from_trainer",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | text-classification | AG6019 | null | null | AG6019/reddit-comment-sentiment-final | 0 | 2 | transformers | 2023-06-01T18:49:42 | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: reddit-comment-sentiment-final
results: []
---
<!-- 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 ... | 1,676 | [
[
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0.0158843994140625,
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-0.04888916015625,
-0.05859375,
-0.00939... |
peanutacake/autotrain-nes_nl-63520135542 | 2023-06-01T19:04:47.000Z | [
"transformers",
"pytorch",
"safetensors",
"bert",
"token-classification",
"autotrain",
"nl",
"dataset:peanutacake/autotrain-data-nes_nl",
"co2_eq_emissions",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | token-classification | peanutacake | null | null | peanutacake/autotrain-nes_nl-63520135542 | 0 | 2 | transformers | 2023-06-01T19:03:42 | ---
tags:
- autotrain
- token-classification
language:
- nl
widget:
- text: "I love AutoTrain"
datasets:
- peanutacake/autotrain-data-nes_nl
co2_eq_emissions:
emissions: 0.24241091204905035
---
# Model Trained Using AutoTrain
- Problem type: Entity Extraction
- Model ID: 63520135542
- CO2 Emissions (in grams): 0.24... | 1,111 | [
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... |
jayanta/bert-base-uncased-english-sentweet-derogatory | 2023-06-01T20:47:47.000Z | [
"transformers",
"pytorch",
"tensorboard",
"bert",
"text-classification",
"generated_from_trainer",
"license:mit",
"endpoints_compatible",
"region:us"
] | text-classification | jayanta | null | null | jayanta/bert-base-uncased-english-sentweet-derogatory | 0 | 2 | transformers | 2023-06-01T20:20:50 | ---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: bert-base-uncased-english-sentweet-derogatory
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread ... | 2,063 | [
[
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-0.0548095703125,
-0.04840087890625,
-0.013... |
jayanta/microsoft-resnet-50-english-sentweet-derogatory | 2023-06-01T21:10:48.000Z | [
"transformers",
"pytorch",
"tensorboard",
"bert",
"text-classification",
"generated_from_trainer",
"license:mit",
"endpoints_compatible",
"region:us"
] | text-classification | jayanta | null | null | jayanta/microsoft-resnet-50-english-sentweet-derogatory | 0 | 2 | transformers | 2023-06-01T20:57:48 | ---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: microsoft-resnet-50-english-sentweet-derogatory
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofrea... | 2,067 | [
[
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-0.0440673828125,
-0.0068588... |
gcagrici/distilbert-base-uncased-finetuned-emotion | 2023-06-02T01:14:27.000Z | [
"transformers",
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"generated_from_trainer",
"dataset:emotion",
"license:apache-2.0",
"model-index",
"endpoints_compatible",
"region:us"
] | text-classification | gcagrici | null | null | gcagrici/distilbert-base-uncased-finetuned-emotion | 0 | 2 | transformers | 2023-06-02T00:51:56 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- emotion
metrics:
- accuracy
- f1
model-index:
- name: distilbert-base-uncased-finetuned-emotion
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: emotion
type: emotion
config: split... | 1,848 | [
[
-0.03839111328125,
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0.007904052734375,
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-0.059234619140625,
... |
platzi/platzi-distilroberta-base-mrpc-joel-orellana | 2023-06-02T02:20:52.000Z | [
"transformers",
"pytorch",
"tensorboard",
"roberta",
"text-classification",
"generated_from_trainer",
"dataset:glue",
"license:apache-2.0",
"model-index",
"endpoints_compatible",
"region:us"
] | text-classification | platzi | null | null | platzi/platzi-distilroberta-base-mrpc-joel-orellana | 0 | 2 | transformers | 2023-06-02T01:55:26 | ---
license: apache-2.0
tags:
- text-classification
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
widget:
- text: ["Yucaipa owned Dominick 's before selling the chain to Safeway in 1998 for $ 2.5 billion.","Yucaipa bought Dominick's in 1995 for $ 693 million and sold it to Safeway for $ 1.8 billio... | 2,407 | [
[
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0.018341064453125,
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-0.0098876953125,
-0.0033283233642578125,
0.005191802978515625,
0.01102447509765625,
-0.05023193359375,
-0.040924072265625,
-0.055999755859375,
... |
tingtone/jq_emo_distilbert | 2023-06-02T05:22:56.000Z | [
"transformers",
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"generated_from_trainer",
"dataset:emotion",
"license:apache-2.0",
"model-index",
"endpoints_compatible",
"region:us"
] | text-classification | tingtone | null | null | tingtone/jq_emo_distilbert | 2 | 2 | transformers | 2023-06-02T02:25:25 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- emotion
metrics:
- accuracy
model-index:
- name: jq_emo_distilbert
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: emotion
type: emotion
config: split
split: validation
... | 2,235 | [
[
-0.030059814453125,
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0.0104827880859375,
0.005466461181640625,
-0.014190673828125,
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-0.0066375732421875,
-0.0056304931640625,
0.0214996337890625,
0.0160064697265625,
-0.057098388671875,
-0.055267333984375,
-0.04791259765625... |
yoshivo/bert-japanese-ner | 2023-06-02T07:56:04.000Z | [
"transformers",
"pytorch",
"bert",
"token-classification",
"generated_from_trainer",
"license:cc-by-sa-4.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | token-classification | yoshivo | null | null | yoshivo/bert-japanese-ner | 0 | 2 | transformers | 2023-06-02T07:11:02 | ---
license: cc-by-sa-4.0
tags:
- generated_from_trainer
model-index:
- name: bert-japanese-ner
results: []
---
<!-- 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-japanese-n... | 1,423 | [
[
-0.0379638671875,
-0.056243896484375,
0.0183868408203125,
0.0203704833984375,
-0.04034423828125,
-0.0291290283203125,
-0.0234222412109375,
-0.0269317626953125,
0.0198516845703125,
0.032501220703125,
-0.0657958984375,
-0.048797607421875,
-0.057769775390625,
-... |
kristinehara/test_trainer | 2023-06-02T07:53:41.000Z | [
"transformers",
"pytorch",
"bert",
"text-classification",
"generated_from_trainer",
"dataset:yelp_review_full",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | text-classification | kristinehara | null | null | kristinehara/test_trainer | 0 | 2 | transformers | 2023-06-02T07:43:35 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- yelp_review_full
model-index:
- name: test_trainer
results: []
---
<!-- 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. ... | 1,026 | [
[
-0.03564453125,
-0.05029296875,
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0.01015472412109375,
-0.031158447265625,
-0.037139892578125,
-0.01267242431640625,
-0.019378662109375,
0.016937255859375,
0.0259552001953125,
-0.0577392578125,
-0.03271484375,
-0.0364990234375,
-0.013847351... |
poltextlab/xlm-roberta-large-dutch-cap | 2023-07-04T17:40:22.000Z | [
"transformers",
"pytorch",
"xlm-roberta",
"text-classification",
"zero-shot-classification",
"nl",
"license:mit",
"endpoints_compatible",
"region:us"
] | text-classification | poltextlab | null | null | poltextlab/xlm-roberta-large-dutch-cap | 0 | 2 | transformers | 2023-06-02T09:11:21 |
---
---
license: mit
language:
- nl
tags:
- zero-shot-classification
- text-classification
- pytorch
metrics:
- accuracy
- f1-score
---
# xlm-roberta-large-dutch-cap
## Model description
An `xlm-roberta-large` model finetuned on dutch training data labelled with [major topic codes](https://www.comparativeagendas.net/p... | 5,554 | [
[
-0.044189453125,
-0.0472412109375,
0.0054931640625,
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0.022430419921875,
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-0.047698974609375,
-0.0550537109375,
0.0... |
fredymad/bert_Pfinal_4CLASES_2e-5_16_2 | 2023-06-02T10:50:29.000Z | [
"transformers",
"pytorch",
"tensorboard",
"bert",
"text-classification",
"generated_from_trainer",
"endpoints_compatible",
"region:us"
] | text-classification | fredymad | null | null | fredymad/bert_Pfinal_4CLASES_2e-5_16_2 | 0 | 2 | transformers | 2023-06-02T09:59:35 | ---
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: bert_Pfinal_4CLASES_2e-5_16_2
results: []
---
<!-- 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_... | 1,437 | [
[
-0.034088134765625,
-0.044891357421875,
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0.023681640625,
-0.0301513671875,
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-0.02398681640625,
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0.016021728515625,
-0.05548095703125,
-0.048248291015625,
-0.04632568359375,
-0.0... |
fredymad/bert_Pfinal_4CLASES_2e-5_16_10 | 2023-06-02T11:45:37.000Z | [
"transformers",
"pytorch",
"tensorboard",
"bert",
"text-classification",
"generated_from_trainer",
"endpoints_compatible",
"region:us"
] | text-classification | fredymad | null | null | fredymad/bert_Pfinal_4CLASES_2e-5_16_10 | 0 | 2 | transformers | 2023-06-02T10:12:44 | ---
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: bert_Pfinal_4CLASES_2e-5_16_10
results: []
---
<!-- 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... | 1,934 | [
[
-0.041534423828125,
-0.03973388671875,
0.0124664306640625,
0.0117340087890625,
-0.0189361572265625,
-0.0272674560546875,
-0.0091094970703125,
-0.017822265625,
0.0188140869140625,
0.0187225341796875,
-0.054595947265625,
-0.0438232421875,
-0.046142578125,
-0.0... |
poltextlab/xlm-roberta-large-spanish-cap | 2023-07-04T17:40:24.000Z | [
"transformers",
"pytorch",
"xlm-roberta",
"text-classification",
"zero-shot-classification",
"es",
"license:mit",
"endpoints_compatible",
"region:us"
] | text-classification | poltextlab | null | null | poltextlab/xlm-roberta-large-spanish-cap | 0 | 2 | transformers | 2023-06-02T10:33:45 |
---
---
license: mit
language:
- es
tags:
- zero-shot-classification
- text-classification
- pytorch
metrics:
- accuracy
- f1-score
---
# xlm-roberta-large-spanish-cap
## Model description
An `xlm-roberta-large` model finetuned on spanish training data labelled with [major topic codes](https://www.comparativeagendas.n... | 5,630 | [
[
-0.042236328125,
-0.046875,
0.004444122314453125,
0.02435302734375,
-0.002532958984375,
-0.0006422996520996094,
-0.02362060546875,
-0.0252838134765625,
0.0176239013671875,
0.0206756591796875,
-0.03790283203125,
-0.048370361328125,
-0.052703857421875,
0.00884... |
poltextlab/xlm-roberta-large-hungarian-cap | 2023-07-04T17:40:25.000Z | [
"transformers",
"pytorch",
"xlm-roberta",
"text-classification",
"zero-shot-classification",
"hu",
"license:mit",
"endpoints_compatible",
"region:us"
] | text-classification | poltextlab | null | null | poltextlab/xlm-roberta-large-hungarian-cap | 0 | 2 | transformers | 2023-06-02T10:37:15 |
---
---
license: mit
language:
- hu
tags:
- zero-shot-classification
- text-classification
- pytorch
metrics:
- accuracy
- f1-score
---
# xlm-roberta-large-hungarian-cap
## Model description
An `xlm-roberta-large` model finetuned on hungarian training data labelled with [major topic codes](https://www.comparativeagend... | 5,642 | [
[
-0.043609619140625,
-0.047332763671875,
0.007411956787109375,
0.018280029296875,
-0.00199127197265625,
-0.004302978515625,
-0.0244140625,
-0.0236663818359375,
0.0150909423828125,
0.020965576171875,
-0.03778076171875,
-0.049957275390625,
-0.0538330078125,
0.0... |
fredymad/roberta_Pfinal_4CLASES_2e-5_16_2 | 2023-06-02T15:50:37.000Z | [
"transformers",
"pytorch",
"tensorboard",
"roberta",
"text-classification",
"generated_from_trainer",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | text-classification | fredymad | null | null | fredymad/roberta_Pfinal_4CLASES_2e-5_16_2 | 0 | 2 | transformers | 2023-06-02T11:49:40 | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: roberta_Pfinal_4CLASES_2e-5_16_2
results: []
---
<!-- 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 thi... | 1,445 | [
[
-0.0278472900390625,
-0.046844482421875,
0.01427459716796875,
0.0117645263671875,
-0.0269775390625,
-0.040496826171875,
-0.014556884765625,
-0.017669677734375,
0.002593994140625,
0.0231170654296875,
-0.051544189453125,
-0.0477294921875,
-0.0467529296875,
-0.... |
fredymad/robertuito_4CLASES_Pfinal | 2023-06-02T12:16:13.000Z | [
"transformers",
"pytorch",
"tensorboard",
"roberta",
"text-classification",
"generated_from_trainer",
"endpoints_compatible",
"region:us"
] | text-classification | fredymad | null | null | fredymad/robertuito_4CLASES_Pfinal | 0 | 2 | transformers | 2023-06-02T12:07:35 | ---
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: robertuito_4CLASES_Pfinal
results: []
---
<!-- 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. -->
# robertuit... | 1,425 | [
[
-0.0257720947265625,
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0.0361328125,
-0.0516357421875,
-0.05499267578125,
-0.04656982421875,
-0.... |
GCopoulos/deberta-finetuned-answer-polarity-warmup-f1 | 2023-06-02T13:43:13.000Z | [
"transformers",
"pytorch",
"deberta",
"text-classification",
"generated_from_trainer",
"dataset:glue",
"license:mit",
"model-index",
"endpoints_compatible",
"region:us"
] | text-classification | GCopoulos | null | null | GCopoulos/deberta-finetuned-answer-polarity-warmup-f1 | 0 | 2 | transformers | 2023-06-02T13:23:57 | ---
license: mit
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- f1
model-index:
- name: deberta-finetuned-answer-polarity-warmup-f1
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: glue
type: glue
config: answer_pol
split: valida... | 1,767 | [
[
-0.0282135009765625,
-0.047515869140625,
0.013916015625,
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0.01226043701171875,
0.0149993896484375,
-0.05401611328125,
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-0.049102783203125,
... |
GCopoulos/deberta-finetuned-answer-polarity-5e | 2023-06-02T14:05:16.000Z | [
"transformers",
"pytorch",
"deberta",
"text-classification",
"generated_from_trainer",
"dataset:glue",
"license:mit",
"model-index",
"endpoints_compatible",
"region:us"
] | text-classification | GCopoulos | null | null | GCopoulos/deberta-finetuned-answer-polarity-5e | 0 | 2 | transformers | 2023-06-02T13:49:18 | ---
license: mit
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- f1
model-index:
- name: deberta-finetuned-answer-polarity-5e
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: glue
type: glue
config: answer_pol
split: validation
... | 1,872 | [
[
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0.017303466796875,
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0.01654052734375,
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-0.04345703125,
-0.0516357421875,
-0.01... |
leofn3/modelo_multiclass_teste01 | 2023-06-02T13:55:06.000Z | [
"sentence-transformers",
"pytorch",
"bert",
"setfit",
"text-classification",
"arxiv:2209.11055",
"license:apache-2.0",
"region:us"
] | text-classification | leofn3 | null | null | leofn3/modelo_multiclass_teste01 | 0 | 2 | sentence-transformers | 2023-06-02T13:53:38 | ---
license: apache-2.0
tags:
- setfit
- sentence-transformers
- text-classification
pipeline_tag: text-classification
---
# /var/folders/l0/32nshlfj7rq1xg2dxcjs9y9w0000gn/T/tmpfrcg6j3b/leofn3/modelo_multiclass_teste01
This is a [SetFit model](https://github.com/huggingface/setfit) that can be used for text classific... | 1,675 | [
[
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0.0284881591796875,
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-0.0164031982421875,
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GCopoulos/deberta-finetuned-answer-polarity-7e-adj | 2023-06-02T14:24:27.000Z | [
"transformers",
"pytorch",
"deberta",
"text-classification",
"generated_from_trainer",
"dataset:glue",
"license:mit",
"model-index",
"endpoints_compatible",
"region:us"
] | text-classification | GCopoulos | null | null | GCopoulos/deberta-finetuned-answer-polarity-7e-adj | 0 | 2 | transformers | 2023-06-02T14:16:18 | ---
license: mit
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- f1
model-index:
- name: deberta-finetuned-answer-polarity-7e-adj
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: glue
type: glue
config: answer_pol
split: validatio... | 1,761 | [
[
-0.0276336669921875,
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0.01751708984375,
0.0179901123046875,
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-0.041259765625,
-0.05322265625,
-0.017... |
Guerosharp/dqn-SpaceInvadersNoFrameskip-v4 | 2023-06-02T14:42:41.000Z | [
"stable-baselines3",
"SpaceInvadersNoFrameskip-v4",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | reinforcement-learning | Guerosharp | null | null | Guerosharp/dqn-SpaceInvadersNoFrameskip-v4 | 0 | 2 | stable-baselines3 | 2023-06-02T14:42:12 | ---
library_name: stable-baselines3
tags:
- SpaceInvadersNoFrameskip-v4
- deep-reinforcement-learning
- reinforcement-learning
- stable-baselines3
model-index:
- name: DQN
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: SpaceInvadersNoFrameskip-v4
... | 2,765 | [
[
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-0.035430908203125,
-0.025299072265625,
-0.00... |
Ttonio/distilbert-base-uncased-finetuned-emotion | 2023-06-02T15:00:35.000Z | [
"transformers",
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"generated_from_trainer",
"dataset:emotion",
"license:apache-2.0",
"model-index",
"endpoints_compatible",
"region:us"
] | text-classification | Ttonio | null | null | Ttonio/distilbert-base-uncased-finetuned-emotion | 0 | 2 | transformers | 2023-06-02T14:48:02 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- emotion
metrics:
- accuracy
- f1
model-index:
- name: distilbert-base-uncased-finetuned-emotion
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: emotion
type: emotion
config: split... | 1,846 | [
[
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-... |
GCopoulos/deberta-finetuned-answer-polarity-1e6 | 2023-06-02T15:04:06.000Z | [
"transformers",
"pytorch",
"deberta",
"text-classification",
"generated_from_trainer",
"dataset:glue",
"license:mit",
"model-index",
"endpoints_compatible",
"region:us"
] | text-classification | GCopoulos | null | null | GCopoulos/deberta-finetuned-answer-polarity-1e6 | 0 | 2 | transformers | 2023-06-02T14:53:37 | ---
license: mit
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- f1
model-index:
- name: deberta-finetuned-answer-polarity-1e6
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: glue
type: glue
config: answer_pol
split: validation
... | 1,995 | [
[
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namedotpg/ppo-LunarLander-v2 | 2023-06-03T22:54:32.000Z | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | reinforcement-learning | namedotpg | null | null | namedotpg/ppo-LunarLander-v2 | 0 | 2 | stable-baselines3 | 2023-06-02T15:24:56 | ---
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: LunarLander-v2
... | 784 | [
[
-0.00023484230041503906,
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-... |
GCopoulos/deberta-finetuned-answer-polarity-7e6 | 2023-06-02T15:57:19.000Z | [
"transformers",
"pytorch",
"deberta",
"text-classification",
"generated_from_trainer",
"dataset:glue",
"license:mit",
"model-index",
"endpoints_compatible",
"region:us"
] | text-classification | GCopoulos | null | null | GCopoulos/deberta-finetuned-answer-polarity-7e6 | 0 | 2 | transformers | 2023-06-02T15:50:15 | ---
license: mit
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- f1
model-index:
- name: deberta-finetuned-answer-polarity-7e6
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: glue
type: glue
config: answer_pol
split: validation
... | 1,755 | [
[
-0.0265045166015625,
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-0.01873... |
derguene/carpooling-MiniLM-L12-v2-fr | 2023-06-07T21:34:28.000Z | [
"sentence-transformers",
"pytorch",
"bert",
"setfit",
"text-classification",
"arxiv:2209.11055",
"license:apache-2.0",
"region:us"
] | text-classification | derguene | null | null | derguene/carpooling-MiniLM-L12-v2-fr | 0 | 2 | sentence-transformers | 2023-06-02T16:02:52 | ---
license: apache-2.0
tags:
- setfit
- sentence-transformers
- text-classification
pipeline_tag: text-classification
---
# derguene/carpooling-MiniLM-L12-v2-fr
This is a [SetFit model](https://github.com/huggingface/setfit) that can be used for text classification. The model has been trained using an efficient few-... | 1,561 | [
[
-0.0082244873046875,
-0.054351806640625,
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-0.0230560302734375,
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0.0232391357421875,
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-0.0372314453125,... |
fredymad/HATE_Pfinal_2e-5_16_2 | 2023-06-02T16:15:13.000Z | [
"transformers",
"pytorch",
"tensorboard",
"bert",
"text-classification",
"generated_from_trainer",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | text-classification | fredymad | null | null | fredymad/HATE_Pfinal_2e-5_16_2 | 0 | 2 | transformers | 2023-06-02T16:03:00 | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: HATE_Pfinal_2e-5_16_2
results: []
---
<!-- 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. -->
#... | 1,425 | [
[
-0.044158935546875,
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-0.056640625,
-0.0... |
Surya-3719/distilbert-base-uncased-finetuned-emotion | 2023-06-03T07:36:36.000Z | [
"transformers",
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"generated_from_trainer",
"dataset:emotion",
"license:apache-2.0",
"model-index",
"endpoints_compatible",
"region:us"
] | text-classification | Surya-3719 | null | null | Surya-3719/distilbert-base-uncased-finetuned-emotion | 0 | 2 | transformers | 2023-06-02T16:50:50 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- emotion
metrics:
- accuracy
- f1
model-index:
- name: distilbert-base-uncased-finetuned-emotion
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: emotion
type: emotion
config: split... | 1,848 | [
[
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-0.060089111328125,
... |
Mariamtc/finetuned-twitter-roberta-base-sep2022-tweetcognition | 2023-06-28T22:07:15.000Z | [
"transformers",
"pytorch",
"roberta",
"text-classification",
"generated_from_trainer",
"en",
"license:mit",
"endpoints_compatible",
"region:us"
] | text-classification | Mariamtc | null | null | Mariamtc/finetuned-twitter-roberta-base-sep2022-tweetcognition | 1 | 2 | transformers | 2023-06-02T17:05:52 | ---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: finetuned-twitter-roberta-base-sep2022-tweetcognition
results: []
language:
- en
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and... | 3,148 | [
[
-0.023895263671875,
-0.060760498046875,
0.01375579833984375,
0.01324462890625,
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0.00969696044921875,
0.0186920166015625,
-0.059112548828125,
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-0.05303955078125... |
HasinMDG/X-Sent-Deberta_v3 | 2023-06-02T17:24:41.000Z | [
"sentence-transformers",
"pytorch",
"deberta-v2",
"setfit",
"text-classification",
"arxiv:2209.11055",
"license:apache-2.0",
"region:us"
] | text-classification | HasinMDG | null | null | HasinMDG/X-Sent-Deberta_v3 | 0 | 2 | sentence-transformers | 2023-06-02T17:24:23 | ---
license: apache-2.0
tags:
- setfit
- sentence-transformers
- text-classification
pipeline_tag: text-classification
---
# HasinMDG/X-Sent-Deberta_v3
This is a [SetFit model](https://github.com/huggingface/setfit) that can be used for text classification. The model has been trained using an efficient few-shot learn... | 1,541 | [
[
-0.004150390625,
-0.060516357421875,
0.03399658203125,
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0.036590576171875,
-0.047393798828125,
-0.0259552001953125,
-0.048492431640625,
... |
GCopoulos/deberta-finetuned-answer-polarity-3e6-newdata3 | 2023-06-02T18:36:56.000Z | [
"transformers",
"pytorch",
"deberta",
"text-classification",
"generated_from_trainer",
"dataset:glue",
"license:mit",
"model-index",
"endpoints_compatible",
"region:us"
] | text-classification | GCopoulos | null | null | GCopoulos/deberta-finetuned-answer-polarity-3e6-newdata3 | 0 | 2 | transformers | 2023-06-02T18:24:51 | ---
license: mit
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- f1
model-index:
- name: deberta-finetuned-answer-polarity-3e6-newdata3
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: glue
type: glue
config: answer_pol
split: val... | 1,773 | [
[
-0.02679443359375,
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0.017181396484375,
-0.052093505859375,
-0.041015625,
-0.0531005859375,
-0.016... |
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