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refilwetabohane/whisper-small-english | refilwetabohane | 2023-11-29T05:09:24Z | 0 | 0 | null | [
"region:us"
] | 2023-11-29T05:09:24Z | 2023-11-29T05:09:24.000Z | null | null | Entry not found | null | null | null | null | null | null | null | null | null | null | null | null | refilwetabohane/whisper-small-english | [
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hkivancoral/hushem_5x_beit_base_rms_001_fold5 | hkivancoral | 2023-11-29T05:43:01Z | 0 | 0 | null | [
"transformers",
"tensorboard",
"safetensors",
"beit",
"image-classification",
"generated_from_trainer",
"dataset:imagefolder",
"base_model:microsoft/beit-base-patch16-224",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | 2023-11-29T05:43:01Z | 2023-11-29T05:10:26.000Z | null | null | ---
license: apache-2.0
base_model: microsoft/beit-base-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: hushem_5x_beit_base_rms_001_fold5
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: imagefolder
type: imagefolder
config: default
split: test
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.34146341463414637
---
<!-- 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. -->
# hushem_5x_beit_base_rms_001_fold5
This model is a fine-tuned version of [microsoft/beit-base-patch16-224](https://huggingface.co/microsoft/beit-base-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 2.4962
- Accuracy: 0.3415
## 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:
- learning_rate: 0.001
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 50
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.501 | 1.0 | 28 | 1.3919 | 0.2439 |
| 1.3993 | 2.0 | 56 | 1.4008 | 0.2683 |
| 1.4258 | 3.0 | 84 | 1.4098 | 0.2439 |
| 1.4011 | 4.0 | 112 | 1.3674 | 0.2683 |
| 1.4153 | 5.0 | 140 | 1.3306 | 0.2683 |
| 1.3649 | 6.0 | 168 | 1.4784 | 0.2195 |
| 1.3525 | 7.0 | 196 | 1.2906 | 0.4390 |
| 1.3374 | 8.0 | 224 | 1.1798 | 0.5122 |
| 1.2661 | 9.0 | 252 | 1.3479 | 0.5122 |
| 1.3011 | 10.0 | 280 | 1.3054 | 0.4878 |
| 1.2212 | 11.0 | 308 | 1.1612 | 0.5122 |
| 1.2579 | 12.0 | 336 | 1.2572 | 0.2683 |
| 1.2438 | 13.0 | 364 | 1.1160 | 0.4634 |
| 1.2218 | 14.0 | 392 | 1.1291 | 0.4878 |
| 1.2455 | 15.0 | 420 | 1.4587 | 0.4390 |
| 1.2528 | 16.0 | 448 | 1.3009 | 0.5122 |
| 1.2445 | 17.0 | 476 | 1.1915 | 0.5122 |
| 1.1729 | 18.0 | 504 | 1.3461 | 0.4390 |
| 1.2917 | 19.0 | 532 | 1.3956 | 0.3659 |
| 1.2335 | 20.0 | 560 | 1.1161 | 0.4146 |
| 1.1787 | 21.0 | 588 | 1.4220 | 0.4390 |
| 1.1076 | 22.0 | 616 | 1.2157 | 0.5122 |
| 1.1837 | 23.0 | 644 | 1.2878 | 0.4634 |
| 1.065 | 24.0 | 672 | 1.3373 | 0.3659 |
| 1.0753 | 25.0 | 700 | 1.2968 | 0.4634 |
| 1.0288 | 26.0 | 728 | 1.2996 | 0.4146 |
| 1.0679 | 27.0 | 756 | 1.2975 | 0.3902 |
| 1.0591 | 28.0 | 784 | 1.3051 | 0.4634 |
| 1.0148 | 29.0 | 812 | 1.2575 | 0.5854 |
| 1.0668 | 30.0 | 840 | 1.3174 | 0.3415 |
| 0.9767 | 31.0 | 868 | 1.3259 | 0.4390 |
| 0.9254 | 32.0 | 896 | 1.3236 | 0.4878 |
| 0.9064 | 33.0 | 924 | 1.5265 | 0.3902 |
| 0.9504 | 34.0 | 952 | 1.2456 | 0.4390 |
| 0.8534 | 35.0 | 980 | 1.2811 | 0.5122 |
| 0.8361 | 36.0 | 1008 | 1.2101 | 0.6098 |
| 0.7846 | 37.0 | 1036 | 1.3727 | 0.4390 |
| 0.7661 | 38.0 | 1064 | 1.4030 | 0.4878 |
| 0.8237 | 39.0 | 1092 | 1.3385 | 0.4634 |
| 0.7652 | 40.0 | 1120 | 1.6174 | 0.4146 |
| 0.6764 | 41.0 | 1148 | 1.6358 | 0.4390 |
| 0.5675 | 42.0 | 1176 | 1.7675 | 0.4390 |
| 0.5777 | 43.0 | 1204 | 1.8573 | 0.4390 |
| 0.5704 | 44.0 | 1232 | 2.0252 | 0.3902 |
| 0.5677 | 45.0 | 1260 | 2.0725 | 0.3902 |
| 0.4676 | 46.0 | 1288 | 2.4159 | 0.3171 |
| 0.4167 | 47.0 | 1316 | 2.4083 | 0.3415 |
| 0.416 | 48.0 | 1344 | 2.4826 | 0.3415 |
| 0.3715 | 49.0 | 1372 | 2.4962 | 0.3415 |
| 0.368 | 50.0 | 1400 | 2.4962 | 0.3415 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
| null | transformers | image-classification | null | null | null | null | null | null | null | null | null | hkivancoral/hushem_5x_beit_base_rms_001_fold5 | [
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yongiant/backup | yongiant | 2023-11-29T05:11:07Z | 0 | 0 | null | [
"region:us"
] | 2023-11-29T05:11:07Z | 2023-11-29T05:11:07.000Z | null | null | Entry not found | null | null | null | null | null | null | null | null | null | null | null | null | yongiant/backup | [
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zacboy326/FelixTheCat_ThomAdcox-Hernandez | zacboy326 | 2023-11-29T05:13:05Z | 0 | 0 | null | [
"region:us"
] | 2023-11-29T05:13:05Z | 2023-11-29T05:12:35.000Z | null | null | Entry not found | null | null | null | null | null | null | null | null | null | null | null | null | zacboy326/FelixTheCat_ThomAdcox-Hernandez | [
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K-kiron/distilbert-batch-size-32 | K-kiron | 2023-11-29T05:15:44Z | 0 | 0 | null | [
"transformers",
"pytorch",
"distilbert",
"text-classification",
"generated_from_trainer",
"base_model:distilbert-base-uncased",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | 2023-11-29T05:15:44Z | 2023-11-29T05:13:19.000Z | null | null | ---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: distilbert-batch-size-32
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. -->
# distilbert-batch-size-32
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0549
- Accuracy: 0.8963
- F1: 0.8963
## 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:
- learning_rate: 2e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
### Training results
### Framework versions
- Transformers 4.32.1
- Pytorch 2.1.1+cu121
- Datasets 2.12.0
- Tokenizers 0.13.3
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Ping2/doctor-falcon-7b | Ping2 | 2023-11-29T06:35:57Z | 0 | 0 | null | [
"region:us"
] | 2023-11-29T06:35:57Z | 2023-11-29T05:14:50.000Z | null | null | Entry not found | null | null | null | null | null | null | null | null | null | null | null | null | Ping2/doctor-falcon-7b | [
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comrad/AskSam | comrad | 2023-11-29T05:15:44Z | 0 | 0 | null | [
"region:us"
] | 2023-11-29T05:15:44Z | 2023-11-29T05:15:44.000Z | null | null | Entry not found | null | null | null | null | null | null | null | null | null | null | null | null | comrad/AskSam | [
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mzyil/llama-2-7b-mzyil | mzyil | 2023-11-29T05:21:23Z | 0 | 0 | null | [
"region:us"
] | 2023-11-29T05:21:23Z | 2023-11-29T05:21:23.000Z | null | null | Entry not found | null | null | null | null | null | null | null | null | null | null | null | null | mzyil/llama-2-7b-mzyil | [
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K-kiron/distilbert-lr-linear | K-kiron | 2023-11-29T05:26:39Z | 0 | 0 | null | [
"transformers",
"pytorch",
"distilbert",
"text-classification",
"generated_from_trainer",
"base_model:distilbert-base-uncased",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | 2023-11-29T05:26:39Z | 2023-11-29T05:23:43.000Z | null | null | ---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: distilbert-lr-linear
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. -->
# distilbert-lr-linear
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1209
- Accuracy: 0.8961
- F1: 0.8962
## 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:
- learning_rate: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
### Training results
### Framework versions
- Transformers 4.32.1
- Pytorch 2.1.1+cu121
- Datasets 2.12.0
- Tokenizers 0.13.3
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dmmagdal/flan-t5-base-onnx | dmmagdal | 2023-11-29T05:32:39Z | 0 | 0 | null | [
"transformers",
"onnx",
"t5",
"text2text-generation",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | 2023-11-29T05:32:39Z | 2023-11-29T05:24:51.000Z | null | null | ---
license: apache-2.0
---
| null | transformers | text2text-generation | null | null | null | null | null | null | null | null | null | dmmagdal/flan-t5-base-onnx | [
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technocrat3128/openhermes-mistral-finetuned-L4 | technocrat3128 | 2023-11-29T10:49:46Z | 0 | 0 | null | [
"tensorboard",
"generated_from_trainer",
"base_model:TheBloke/OpenHermes-2.5-Mistral-7B-GPTQ",
"license:apache-2.0",
"region:us"
] | 2023-11-29T10:49:46Z | 2023-11-29T05:29:00.000Z | null | null | ---
license: apache-2.0
base_model: TheBloke/OpenHermes-2.5-Mistral-7B-GPTQ
tags:
- generated_from_trainer
model-index:
- name: openhermes-mistral-finetuned-L4
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. -->
# openhermes-mistral-finetuned-L4
This model is a fine-tuned version of [TheBloke/OpenHermes-2.5-Mistral-7B-GPTQ](https://huggingface.co/TheBloke/OpenHermes-2.5-Mistral-7B-GPTQ) on the None dataset.
## 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:
- learning_rate: 0.0002
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 5
- mixed_precision_training: Native AMP
### Training results
### Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.15.0
| null | null | null | null | null | null | null | null | null | null | null | null | technocrat3128/openhermes-mistral-finetuned-L4 | [
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mcfatbeard/flant5-large | mcfatbeard | 2023-11-29T08:25:51Z | 0 | 0 | null | [
"tensorboard",
"region:us"
] | 2023-11-29T08:25:51Z | 2023-11-29T05:29:17.000Z | null | null | Entry not found | null | null | null | null | null | null | null | null | null | null | null | null | mcfatbeard/flant5-large | [
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Jeevesh8/multibert_seed0_0k_qqp_ft_58 | Jeevesh8 | 2023-11-29T13:55:14Z | 0 | 0 | null | [
"transformers",
"jax",
"tensorboard",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] | 2023-11-29T13:55:14Z | 2023-11-29T05:29:30.000Z | null | null | Entry not found | null | transformers | text-classification | null | null | null | null | null | null | null | null | null | Jeevesh8/multibert_seed0_0k_qqp_ft_58 | [
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Jeevesh8/multibert_seed0_0k_qqp_ft_57 | Jeevesh8 | 2023-11-29T13:54:38Z | 0 | 0 | null | [
"transformers",
"jax",
"tensorboard",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] | 2023-11-29T13:54:38Z | 2023-11-29T05:29:30.000Z | null | null | Entry not found | null | transformers | text-classification | null | null | null | null | null | null | null | null | null | Jeevesh8/multibert_seed0_0k_qqp_ft_57 | [
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Jeevesh8/multibert_seed0_0k_qqp_ft_55 | Jeevesh8 | 2023-11-29T13:55:27Z | 0 | 0 | null | [
"transformers",
"jax",
"tensorboard",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] | 2023-11-29T13:55:27Z | 2023-11-29T05:29:30.000Z | null | null | Entry not found | null | transformers | text-classification | null | null | null | null | null | null | null | null | null | Jeevesh8/multibert_seed0_0k_qqp_ft_55 | [
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Jeevesh8/multibert_seed0_0k_qqp_ft_59 | Jeevesh8 | 2023-11-29T13:53:45Z | 0 | 0 | null | [
"transformers",
"jax",
"tensorboard",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] | 2023-11-29T13:53:45Z | 2023-11-29T05:29:31.000Z | null | null | Entry not found | null | transformers | text-classification | null | null | null | null | null | null | null | null | null | Jeevesh8/multibert_seed0_0k_qqp_ft_59 | [
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Jeevesh8/multibert_seed0_0k_qqp_ft_50 | Jeevesh8 | 2023-11-29T13:55:48Z | 0 | 0 | null | [
"transformers",
"jax",
"tensorboard",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] | 2023-11-29T13:55:48Z | 2023-11-29T05:29:31.000Z | null | null | Entry not found | null | transformers | text-classification | null | null | null | null | null | null | null | null | null | Jeevesh8/multibert_seed0_0k_qqp_ft_50 | [
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Jeevesh8/multibert_seed0_0k_qqp_ft_56 | Jeevesh8 | 2023-11-29T13:52:39Z | 0 | 0 | null | [
"transformers",
"jax",
"tensorboard",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] | 2023-11-29T13:52:39Z | 2023-11-29T05:29:31.000Z | null | null | Entry not found | null | transformers | text-classification | null | null | null | null | null | null | null | null | null | Jeevesh8/multibert_seed0_0k_qqp_ft_56 | [
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Jeevesh8/multibert_seed0_0k_qqp_ft_53 | Jeevesh8 | 2023-11-29T14:13:44Z | 0 | 0 | null | [
"transformers",
"jax",
"tensorboard",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] | 2023-11-29T14:13:44Z | 2023-11-29T05:29:31.000Z | null | null | Entry not found | null | transformers | text-classification | null | null | null | null | null | null | null | null | null | Jeevesh8/multibert_seed0_0k_qqp_ft_53 | [
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Jeevesh8/multibert_seed0_0k_qqp_ft_52 | Jeevesh8 | 2023-11-29T13:50:01Z | 0 | 0 | null | [
"transformers",
"jax",
"tensorboard",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] | 2023-11-29T13:50:01Z | 2023-11-29T05:29:32.000Z | null | null | Entry not found | null | transformers | text-classification | null | null | null | null | null | null | null | null | null | Jeevesh8/multibert_seed0_0k_qqp_ft_52 | [
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Jeevesh8/multibert_seed0_0k_qqp_ft_51 | Jeevesh8 | 2023-11-29T13:47:06Z | 0 | 0 | null | [
"transformers",
"jax",
"tensorboard",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] | 2023-11-29T13:47:06Z | 2023-11-29T05:29:33.000Z | null | null | Entry not found | null | transformers | text-classification | null | null | null | null | null | null | null | null | null | Jeevesh8/multibert_seed0_0k_qqp_ft_51 | [
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Jeevesh8/multibert_seed0_0k_qqp_ft_54 | Jeevesh8 | 2023-11-29T13:37:04Z | 0 | 0 | null | [
"transformers",
"jax",
"tensorboard",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] | 2023-11-29T13:37:04Z | 2023-11-29T05:29:33.000Z | null | null | Entry not found | null | transformers | text-classification | null | null | null | null | null | null | null | null | null | Jeevesh8/multibert_seed0_0k_qqp_ft_54 | [
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try-willaner-skin-tag-remover/willaner-skin-tag-remover | try-willaner-skin-tag-remover | 2023-11-29T05:32:26Z | 0 | 0 | null | [
"diffusers",
"Willaner Skin Tag Remover",
"en",
"license:cc-by-sa-4.0",
"region:us"
] | 2023-11-29T05:32:26Z | 2023-11-29T05:30:27.000Z | null | null | ---
license: cc-by-sa-4.0
language:
- en
library_name: diffusers
tags:
- Willaner Skin Tag Remover
---
[Willaner Skin Tag Remover](https://atozsupplement.com/willaner-skin-tag-remover/) Anti-aging serums are skincare items intended to target indications of aging like kinks, scarcely discernible differences, and loss of versatility. They frequently contain dynamic fixings like retinoids, peptides, hyaluronic corrosive, antioxidants, and nutrients. These parts work to hydrate the skin, animate collagen creation, and lessen the presence of kinks. While picking a serum, consider your skin type and worries to find one that suits you best. Continuously make sure to fix test and bring new items steadily into your skincare routine to guarantee they function admirably with your skin.
VISIT HERE FOR OFFICIAL WEBSITE:-https://atozsupplement.com/willaner-skin-tag-remover/ | null | diffusers | null | null | null | null | null | null | null | null | null | null | try-willaner-skin-tag-remover/willaner-skin-tag-remover | [
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unsloth/llama-2-7b-4bit | unsloth | 2023-11-29T16:56:35Z | 0 | 0 | null | [
"license:llama2",
"region:us"
] | 2023-11-29T16:56:35Z | 2023-11-29T05:31:08.000Z | null | null | ---
license: llama2
---
Will add a 4bit quantized upload once https://github.com/huggingface/transformers/pull/26037 gets merged. | null | null | null | null | null | null | null | null | null | null | null | null | unsloth/llama-2-7b-4bit | [
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rechido/20231129_online_2task_epoch100 | rechido | 2023-11-29T06:23:31Z | 0 | 0 | null | [
"diffusers",
"diffusers:DDPMPipeline",
"region:us"
] | 2023-11-29T06:23:31Z | 2023-11-29T05:31:11.000Z | null | null | Entry not found | null | diffusers | null | null | null | null | null | null | null | null | null | null | rechido/20231129_online_2task_epoch100 | [
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dikshyamohanty/sample | dikshyamohanty | 2023-11-29T05:32:12Z | 0 | 0 | null | [
"region:us"
] | 2023-11-29T05:32:12Z | 2023-11-29T05:32:12.000Z | null | null | Entry not found | null | null | null | null | null | null | null | null | null | null | null | null | dikshyamohanty/sample | [
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AI-Wheelz/Cornel2024 | AI-Wheelz | 2023-11-29T05:33:51Z | 0 | 0 | null | [
"license:openrail",
"region:us"
] | 2023-11-29T05:33:51Z | 2023-11-29T05:32:13.000Z | null | null | ---
license: openrail
---
| null | null | null | null | null | null | null | null | null | null | null | null | AI-Wheelz/Cornel2024 | [
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HDZ12/HDZ | HDZ12 | 2023-11-29T05:35:17Z | 0 | 0 | null | [
"license:apache-2.0",
"region:us"
] | 2023-11-29T05:35:17Z | 2023-11-29T05:35:17.000Z | null | null | ---
license: apache-2.0
---
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zxmboii/RVCModels | zxmboii | 2023-11-29T05:48:09Z | 0 | 0 | null | [
"license:openrail",
"region:us"
] | 2023-11-29T05:48:09Z | 2023-11-29T05:35:39.000Z | null | null | ---
license: openrail
---
| null | null | null | null | null | null | null | null | null | null | null | null | zxmboii/RVCModels | [
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danielhanchen/llama-2-7b-4bit | danielhanchen | 2023-11-29T05:36:53Z | 0 | 0 | null | [
"region:us"
] | 2023-11-29T05:36:53Z | 2023-11-29T05:36:52.000Z | null | null | Entry not found | null | null | null | null | null | null | null | null | null | null | null | null | danielhanchen/llama-2-7b-4bit | [
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Rigosaenz/bowsersml | Rigosaenz | 2023-11-29T05:41:18Z | 0 | 0 | null | [
"license:openrail",
"region:us"
] | 2023-11-29T05:41:18Z | 2023-11-29T05:40:09.000Z | null | null | ---
license: openrail
---
| null | null | null | null | null | null | null | null | null | null | null | null | Rigosaenz/bowsersml | [
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espnet/acesinger_opencpop_visinger2_44khz | espnet | 2023-11-29T05:41:15Z | 0 | 0 | null | [
"espnet",
"audio",
"singing-voice-synthesis",
"zh",
"dataset:acesinger",
"arxiv:1804.00015",
"license:cc-by-4.0",
"region:us"
] | 2023-11-29T05:41:15Z | 2023-11-29T05:40:43.000Z | null | null | ---
tags:
- espnet
- audio
- singing-voice-synthesis
language: zh
datasets:
- acesinger
license: cc-by-4.0
---
## ESPnet2 SVS model
### `espnet/acesinger_opencpop_visinger2_44khz`
This model was trained by ftshijt using acesinger recipe in [espnet](https://github.com/espnet/espnet/).
### Demo: How to use in ESPnet2
Follow the [ESPnet installation instructions](https://espnet.github.io/espnet/installation.html)
if you haven't done that already.
```bash
cd espnet
git checkout 5c4d7cf7feba8461de2e1080bf82182f0efaef38
pip install -e .
cd egs2/acesinger/svs1
./run.sh --skip_data_prep false --skip_train true --download_model espnet/acesinger_opencpop_visinger2_44khz
```
## SVS config
<details><summary>expand</summary>
```
config: conf/tuning/train_visinger2.yaml
print_config: false
log_level: INFO
drop_last_iter: false
dry_run: false
iterator_type: sequence
valid_iterator_type: null
output_dir: exp/svs_train_visinger2_raw_phn_None_zh
ngpu: 1
seed: 777
num_workers: 0
num_att_plot: 0
dist_backend: nccl
dist_init_method: env://
dist_world_size: null
dist_rank: null
local_rank: 0
dist_master_addr: null
dist_master_port: null
dist_launcher: null
multiprocessing_distributed: false
unused_parameters: true
sharded_ddp: false
cudnn_enabled: true
cudnn_benchmark: false
cudnn_deterministic: false
collect_stats: false
write_collected_feats: false
max_epoch: 500
patience: null
val_scheduler_criterion:
- valid
- loss
early_stopping_criterion:
- valid
- loss
- min
best_model_criterion:
- - train
- total_count
- max
keep_nbest_models: 10
nbest_averaging_interval: 0
grad_clip: -1
grad_clip_type: 2.0
grad_noise: false
accum_grad: 1
no_forward_run: false
resume: true
train_dtype: float32
use_amp: false
log_interval: 50
use_matplotlib: true
use_tensorboard: true
create_graph_in_tensorboard: false
use_wandb: false
wandb_project: null
wandb_id: null
wandb_entity: null
wandb_name: null
wandb_model_log_interval: -1
detect_anomaly: false
use_lora: false
save_lora_only: true
lora_conf: {}
pretrain_path: null
init_param: []
ignore_init_mismatch: false
freeze_param: []
num_iters_per_epoch: 1000
batch_size: 8
valid_batch_size: null
batch_bins: 1000000
valid_batch_bins: null
train_shape_file:
- exp/svs_stats_raw_phn_None_zh/train/text_shape.phn
- exp/svs_stats_raw_phn_None_zh/train/singing_shape
valid_shape_file:
- exp/svs_stats_raw_phn_None_zh/valid/text_shape.phn
- exp/svs_stats_raw_phn_None_zh/valid/singing_shape
batch_type: sorted
valid_batch_type: null
fold_length:
- 150
- 409600
sort_in_batch: descending
shuffle_within_batch: false
sort_batch: descending
multiple_iterator: false
chunk_length: 500
chunk_shift_ratio: 0.5
num_cache_chunks: 1024
chunk_excluded_key_prefixes: []
train_data_path_and_name_and_type:
- - dump/raw/tr_no_dev/text
- text
- text
- - dump/raw/tr_no_dev/wav.scp
- singing
- sound
- - dump/raw/tr_no_dev/label
- label
- duration
- - dump/raw/tr_no_dev/score.scp
- score
- score
- - exp/svs_stats_raw_phn_None_zh/train/collect_feats/pitch.scp
- pitch
- npy
- - exp/svs_stats_raw_phn_None_zh/train/collect_feats/feats.scp
- feats
- npy
- - dump/raw/tr_no_dev/utt2sid
- sids
- text_int
valid_data_path_and_name_and_type:
- - dump/raw/dev/text
- text
- text
- - dump/raw/dev/wav.scp
- singing
- sound
- - dump/raw/dev/label
- label
- duration
- - dump/raw/dev/score.scp
- score
- score
- - exp/svs_stats_raw_phn_None_zh/valid/collect_feats/pitch.scp
- pitch
- npy
- - exp/svs_stats_raw_phn_None_zh/valid/collect_feats/feats.scp
- feats
- npy
- - dump/raw/dev/utt2sid
- sids
- text_int
allow_variable_data_keys: false
max_cache_size: 0.0
max_cache_fd: 32
allow_multi_rates: false
valid_max_cache_size: null
exclude_weight_decay: false
exclude_weight_decay_conf: {}
optim: adamw
optim_conf:
lr: 0.0002
betas:
- 0.8
- 0.99
eps: 1.0e-09
weight_decay: 0.0
scheduler: exponentiallr
scheduler_conf:
gamma: 0.998
optim2: adamw
optim2_conf:
lr: 0.0002
betas:
- 0.8
- 0.99
eps: 1.0e-09
weight_decay: 0.0
scheduler2: exponentiallr
scheduler2_conf:
gamma: 0.998
generator_first: true
token_list:
- <blank>
- <unk>
- SP
- i
- AP
- e
- d
- y
- w
- sh
- ai
- n
- x
- j
- u
- ian
- l
- h
- b
- o
- zh
- ou
- an
- m
- q
- z
- en
- g
- ing
- ei
- ao
- uo
- ang
- eng
- t
- ong
- a
- ui
- f
- k
- r
- ch
- v
- iang
- in
- iao
- ie
- iu
- c
- s
- van
- p
- ve
- uan
- uang
- ia
- ua
- uai
- un
- er
- vn
- iong
- <sos/eos>
odim: null
model_conf: {}
use_preprocessor: true
token_type: phn
bpemodel: null
non_linguistic_symbols: null
cleaner: null
g2p: null
fs: 44100
score_feats_extract: syllable_score_feats
score_feats_extract_conf:
fs: 44100
n_fft: 2048
win_length: 2048
hop_length: 512
feats_extract: fbank
feats_extract_conf:
n_fft: 2048
hop_length: 512
win_length: 2048
fs: 44100
fmin: 80
fmax: 7600
n_mels: 80
normalize: global_mvn
normalize_conf:
stats_file: exp/svs_stats_raw_phn_None_zh/train/feats_stats.npz
svs: vits
svs_conf:
generator_type: visinger2
vocoder_generator_type: visinger2
generator_params:
hidden_channels: 192
spks: 31
global_channels: 256
segment_size: 20
text_encoder_attention_heads: 2
text_encoder_ffn_expand: 4
text_encoder_blocks: 6
text_encoder_positionwise_layer_type: conv1d
text_encoder_positionwise_conv_kernel_size: 3
text_encoder_positional_encoding_layer_type: rel_pos
text_encoder_self_attention_layer_type: rel_selfattn
text_encoder_activation_type: swish
text_encoder_normalize_before: true
text_encoder_dropout_rate: 0.1
text_encoder_positional_dropout_rate: 0.0
text_encoder_attention_dropout_rate: 0.1
use_macaron_style_in_text_encoder: true
use_conformer_conv_in_text_encoder: false
text_encoder_conformer_kernel_size: -1
decoder_kernel_size: 7
decoder_channels: 256
decoder_upsample_scales:
- 8
- 8
- 4
- 2
decoder_upsample_kernel_sizes:
- 16
- 16
- 8
- 4
n_harmonic: 64
decoder_resblock_kernel_sizes:
- 3
- 7
- 11
decoder_resblock_dilations:
- - 1
- 3
- 5
- - 1
- 3
- 5
- - 1
- 3
- 5
use_weight_norm_in_decoder: true
posterior_encoder_kernel_size: 3
posterior_encoder_layers: 8
posterior_encoder_stacks: 1
posterior_encoder_base_dilation: 1
posterior_encoder_dropout_rate: 0.0
use_weight_norm_in_posterior_encoder: true
flow_flows: -1
flow_kernel_size: 5
flow_base_dilation: 1
flow_layers: 4
flow_dropout_rate: 0.0
use_weight_norm_in_flow: true
use_only_mean_in_flow: true
use_phoneme_predictor: false
vocabs: 63
aux_channels: 80
generator_type: visinger2
vocoder_generator_type: visinger2
fs: 44100
hop_length: 512
win_length: 2048
n_fft: 2048
discriminator_type: visinger2
discriminator_params:
scales: 1
scale_downsample_pooling: AvgPool1d
scale_downsample_pooling_params:
kernel_size: 4
stride: 2
padding: 2
scale_discriminator_params:
in_channels: 1
out_channels: 1
kernel_sizes:
- 15
- 41
- 5
- 3
channels: 128
max_downsample_channels: 1024
max_groups: 256
bias: true
downsample_scales:
- 4
- 4
- 4
- 4
nonlinear_activation: LeakyReLU
nonlinear_activation_params:
negative_slope: 0.1
use_weight_norm: true
use_spectral_norm: false
follow_official_norm: false
periods:
- 2
- 3
- 5
- 7
- 11
period_discriminator_params:
in_channels: 1
out_channels: 1
kernel_sizes:
- 5
- 3
channels: 32
downsample_scales:
- 3
- 3
- 3
- 3
- 1
max_downsample_channels: 1024
bias: true
nonlinear_activation: LeakyReLU
nonlinear_activation_params:
negative_slope: 0.1
use_weight_norm: true
use_spectral_norm: false
multi_freq_disc_params:
hidden_channels:
- 256
- 256
- 256
- 256
- 256
domain: double
mel_scale: true
divisors:
- 32
- 16
- 8
- 4
- 2
- 1
- 1
strides:
- 1
- 2
- 1
- 2
- 1
- 2
- 1
sample_rate: 44100
hop_lengths:
- 110
- 220
- 330
- 441
- 551
- 661
generator_adv_loss_params:
average_by_discriminators: false
loss_type: mse
discriminator_adv_loss_params:
average_by_discriminators: false
loss_type: mse
feat_match_loss_params:
average_by_discriminators: false
average_by_layers: false
include_final_outputs: true
mel_loss_params:
fs: 44100
n_fft: 2048
hop_length: 512
win_length: 2048
window: hann
n_mels: 80
fmin: 0
fmax: 22050
log_base: null
lambda_adv: 1.0
lambda_mel: 45.0
lambda_feat_match: 2.0
lambda_dur: 0.1
lambda_pitch: 10.0
lambda_phoneme: 1.0
lambda_kl: 1.0
sampling_rate: 44100
cache_generator_outputs: true
pitch_extract: dio
pitch_extract_conf:
use_token_averaged_f0: false
use_log_f0: false
fs: 44100
n_fft: 2048
hop_length: 512
f0max: 800
f0min: 80
pitch_normalize: null
pitch_normalize_conf:
stats_file: exp/svs_stats_raw_phn_None_zh/train/pitch_stats.npz
ying_extract: null
ying_extract_conf: {}
energy_extract: null
energy_extract_conf: {}
energy_normalize: null
energy_normalize_conf: {}
required:
- output_dir
- token_list
version: '202310'
distributed: false
```
</details>
### Citing ESPnet
```BibTex
@inproceedings{watanabe2018espnet,
author={Shinji Watanabe and Takaaki Hori and Shigeki Karita and Tomoki Hayashi and Jiro Nishitoba and Yuya Unno and Nelson Yalta and Jahn Heymann and Matthew Wiesner and Nanxin Chen and Adithya Renduchintala and Tsubasa Ochiai},
title={{ESPnet}: End-to-End Speech Processing Toolkit},
year={2018},
booktitle={Proceedings of Interspeech},
pages={2207--2211},
doi={10.21437/Interspeech.2018-1456},
url={http://dx.doi.org/10.21437/Interspeech.2018-1456}
}
@inproceedings{shi22d_interspeech,
author={Jiatong Shi and Shuai Guo and Tao Qian and Tomoki Hayashi and Yuning Wu and Fangzheng Xu and Xuankai Chang and Huazhe Li and Peter Wu and Shinji Watanabe and Qin Jin},
title={{Muskits: an End-to-end Music Processing Toolkit for Singing Voice Synthesis}},
year=2022,
booktitle={Proc. Interspeech 2022},
pages={4277--4281},
doi={10.21437/Interspeech.2022-10039}
}
```
or arXiv:
```bibtex
@misc{watanabe2018espnet,
title={ESPnet: End-to-End Speech Processing Toolkit},
author={Shinji Watanabe and Takaaki Hori and Shigeki Karita and Tomoki Hayashi and Jiro Nishitoba and Yuya Unno and Nelson Yalta and Jahn Heymann and Matthew Wiesner and Nanxin Chen and Adithya Renduchintala and Tsubasa Ochiai},
year={2018},
eprint={1804.00015},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
```
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jerawincel/albert-base-v2-finetuned | jerawincel | 2023-11-29T23:29:34Z | 0 | 0 | null | [
"transformers",
"tensorboard",
"safetensors",
"albert",
"text-classification",
"endpoints_compatible",
"region:us"
] | 2023-11-29T23:29:34Z | 2023-11-29T05:40:49.000Z | null | null | Entry not found | null | transformers | text-classification | null | null | null | null | null | null | null | null | null | jerawincel/albert-base-v2-finetuned | [
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brettbbb/finetune_arc_1 | brettbbb | 2023-11-29T05:45:29Z | 0 | 0 | null | [
"generated_from_trainer",
"base_model:lmsys/vicuna-7b-v1.5",
"license:llama2",
"region:us"
] | 2023-11-29T05:45:29Z | 2023-11-29T05:41:40.000Z | null | null | ---
license: llama2
base_model: lmsys/vicuna-7b-v1.5
tags:
- generated_from_trainer
model-index:
- name: finetune_arc_1
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. -->
# finetune_arc_1
This model is a fine-tuned version of [lmsys/vicuna-7b-v1.5](https://huggingface.co/lmsys/vicuna-7b-v1.5) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2916
## 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:
- learning_rate: 0.0001
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 5
- num_epochs: 1
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.4948 | 1.0 | 150 | 1.2916 |
### Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.13.1
- Tokenizers 0.14.1
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Anasmob/Pixelcopter-PLE-v0 | Anasmob | 2023-11-29T05:44:23Z | 0 | 0 | null | [
"Pixelcopter-PLE-v0",
"reinforce",
"reinforcement-learning",
"custom-implementation",
"deep-rl-class",
"model-index",
"region:us"
] | 2023-11-29T05:44:23Z | 2023-11-29T05:44:19.000Z | null | null | ---
tags:
- Pixelcopter-PLE-v0
- reinforce
- reinforcement-learning
- custom-implementation
- deep-rl-class
model-index:
- name: Pixelcopter-PLE-v0
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: Pixelcopter-PLE-v0
type: Pixelcopter-PLE-v0
metrics:
- type: mean_reward
value: 21.90 +/- 12.86
name: mean_reward
verified: false
---
# **Reinforce** Agent playing **Pixelcopter-PLE-v0**
This is a trained model of a **Reinforce** agent playing **Pixelcopter-PLE-v0** .
To learn to use this model and train yours check Unit 4 of the Deep Reinforcement Learning Course: https://huggingface.co/deep-rl-course/unit4/introduction
| null | null | reinforcement-learning | null | null | null | null | null | null | null | null | null | Anasmob/Pixelcopter-PLE-v0 | [
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hkivancoral/hushem_5x_beit_base_rms_0001_fold1 | hkivancoral | 2023-11-29T06:17:02Z | 0 | 0 | null | [
"transformers",
"tensorboard",
"safetensors",
"beit",
"image-classification",
"generated_from_trainer",
"dataset:imagefolder",
"base_model:microsoft/beit-base-patch16-224",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | 2023-11-29T06:17:02Z | 2023-11-29T05:45:07.000Z | null | null | ---
license: apache-2.0
base_model: microsoft/beit-base-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: hushem_5x_beit_base_rms_0001_fold1
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: imagefolder
type: imagefolder
config: default
split: test
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.35555555555555557
---
<!-- 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. -->
# hushem_5x_beit_base_rms_0001_fold1
This model is a fine-tuned version of [microsoft/beit-base-patch16-224](https://huggingface.co/microsoft/beit-base-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 3.6811
- Accuracy: 0.3556
## 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:
- learning_rate: 0.0001
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 50
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.4287 | 1.0 | 27 | 1.3926 | 0.2222 |
| 1.3907 | 2.0 | 54 | 1.3975 | 0.2667 |
| 1.358 | 3.0 | 81 | 1.5093 | 0.2444 |
| 1.3416 | 4.0 | 108 | 1.5118 | 0.2444 |
| 1.2056 | 5.0 | 135 | 1.4928 | 0.2444 |
| 1.1299 | 6.0 | 162 | 1.6562 | 0.2222 |
| 1.1641 | 7.0 | 189 | 1.5947 | 0.2444 |
| 1.1473 | 8.0 | 216 | 1.5964 | 0.2444 |
| 1.1298 | 9.0 | 243 | 1.7663 | 0.2444 |
| 1.1045 | 10.0 | 270 | 1.6309 | 0.3778 |
| 0.8985 | 11.0 | 297 | 1.6908 | 0.4 |
| 0.7744 | 12.0 | 324 | 1.3949 | 0.3556 |
| 0.7617 | 13.0 | 351 | 1.4646 | 0.3778 |
| 0.6843 | 14.0 | 378 | 1.5910 | 0.3778 |
| 0.6647 | 15.0 | 405 | 1.8050 | 0.4 |
| 0.6363 | 16.0 | 432 | 1.7016 | 0.3333 |
| 0.6362 | 17.0 | 459 | 1.8539 | 0.3778 |
| 0.6858 | 18.0 | 486 | 1.8678 | 0.3556 |
| 0.7039 | 19.0 | 513 | 1.5776 | 0.3556 |
| 0.6292 | 20.0 | 540 | 1.8552 | 0.3111 |
| 0.4567 | 21.0 | 567 | 1.7854 | 0.3556 |
| 0.5954 | 22.0 | 594 | 2.4822 | 0.3556 |
| 0.5737 | 23.0 | 621 | 2.0564 | 0.4 |
| 0.4941 | 24.0 | 648 | 1.9451 | 0.3111 |
| 0.523 | 25.0 | 675 | 2.0359 | 0.3778 |
| 0.5221 | 26.0 | 702 | 2.1184 | 0.4 |
| 0.4589 | 27.0 | 729 | 2.0471 | 0.3556 |
| 0.4473 | 28.0 | 756 | 2.5353 | 0.3556 |
| 0.4328 | 29.0 | 783 | 2.7479 | 0.3556 |
| 0.4259 | 30.0 | 810 | 2.2239 | 0.3778 |
| 0.3698 | 31.0 | 837 | 2.5363 | 0.3556 |
| 0.3577 | 32.0 | 864 | 2.5264 | 0.3556 |
| 0.3882 | 33.0 | 891 | 2.2649 | 0.3333 |
| 0.3526 | 34.0 | 918 | 2.6438 | 0.3556 |
| 0.2747 | 35.0 | 945 | 2.3584 | 0.3778 |
| 0.2842 | 36.0 | 972 | 2.8515 | 0.3556 |
| 0.2603 | 37.0 | 999 | 2.3416 | 0.3778 |
| 0.2268 | 38.0 | 1026 | 2.7485 | 0.3778 |
| 0.2 | 39.0 | 1053 | 3.3636 | 0.3333 |
| 0.2049 | 40.0 | 1080 | 3.1692 | 0.3333 |
| 0.1369 | 41.0 | 1107 | 3.3885 | 0.3556 |
| 0.1813 | 42.0 | 1134 | 3.3020 | 0.3333 |
| 0.1518 | 43.0 | 1161 | 2.8618 | 0.4 |
| 0.0986 | 44.0 | 1188 | 3.2902 | 0.3778 |
| 0.131 | 45.0 | 1215 | 3.3898 | 0.3333 |
| 0.0809 | 46.0 | 1242 | 3.5629 | 0.3333 |
| 0.048 | 47.0 | 1269 | 3.7516 | 0.3333 |
| 0.038 | 48.0 | 1296 | 3.6814 | 0.3556 |
| 0.0465 | 49.0 | 1323 | 3.6811 | 0.3556 |
| 0.0644 | 50.0 | 1350 | 3.6811 | 0.3556 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
| null | transformers | image-classification | null | null | null | null | null | null | null | null | null | hkivancoral/hushem_5x_beit_base_rms_0001_fold1 | [
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jellyconsumer/falcon-7b-instruct-sharded_large_peft | jellyconsumer | 2023-11-29T05:47:28Z | 0 | 0 | null | [
"region:us"
] | 2023-11-29T05:47:28Z | 2023-11-29T05:47:28.000Z | null | null | Entry not found | null | null | null | null | null | null | null | null | null | null | null | null | jellyconsumer/falcon-7b-instruct-sharded_large_peft | [
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Realgon/roberta_sst2_padding0model | Realgon | 2023-11-29T06:27:37Z | 0 | 0 | null | [
"transformers",
"pytorch",
"roberta",
"text-classification",
"generated_from_trainer",
"base_model:roberta-base",
"license:mit",
"endpoints_compatible",
"region:us"
] | 2023-11-29T06:27:37Z | 2023-11-29T06:01:32.000Z | null | null | ---
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: roberta_sst2_padding0model
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. -->
# roberta_sst2_padding0model
This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4539
- Accuracy: 0.9484
## 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:
- learning_rate: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log | 1.0 | 433 | 0.1891 | 0.9407 |
| 0.3324 | 2.0 | 866 | 0.3948 | 0.9176 |
| 0.1922 | 3.0 | 1299 | 0.2418 | 0.9379 |
| 0.126 | 4.0 | 1732 | 0.3080 | 0.9407 |
| 0.069 | 5.0 | 2165 | 0.4075 | 0.9396 |
| 0.0358 | 6.0 | 2598 | 0.3955 | 0.9418 |
| 0.0298 | 7.0 | 3031 | 0.4060 | 0.9429 |
| 0.0298 | 8.0 | 3464 | 0.4284 | 0.9379 |
| 0.0207 | 9.0 | 3897 | 0.4804 | 0.9401 |
| 0.0197 | 10.0 | 4330 | 0.5089 | 0.9347 |
| 0.0177 | 11.0 | 4763 | 0.5430 | 0.9336 |
| 0.0143 | 12.0 | 5196 | 0.4997 | 0.9385 |
| 0.0138 | 13.0 | 5629 | 0.4695 | 0.9429 |
| 0.0066 | 14.0 | 6062 | 0.5391 | 0.9363 |
| 0.0066 | 15.0 | 6495 | 0.5354 | 0.9412 |
| 0.0042 | 16.0 | 6928 | 0.4295 | 0.9473 |
| 0.0067 | 17.0 | 7361 | 0.4948 | 0.9429 |
| 0.0053 | 18.0 | 7794 | 0.4720 | 0.9473 |
| 0.0041 | 19.0 | 8227 | 0.4552 | 0.9451 |
| 0.0068 | 20.0 | 8660 | 0.4539 | 0.9484 |
### Framework versions
- Transformers 4.32.1
- Pytorch 2.1.1
- Datasets 2.12.0
- Tokenizers 0.13.3
| null | transformers | text-classification | null | null | null | null | null | null | null | null | null | Realgon/roberta_sst2_padding0model | [
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sergioska/autobot-generator | sergioska | 2023-11-29T06:01:48Z | 0 | 0 | null | [
"region:us"
] | 2023-11-29T06:01:48Z | 2023-11-29T06:01:45.000Z | null | null | Entry not found | null | null | null | null | null | null | null | null | null | null | null | null | sergioska/autobot-generator | [
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lol-cod/captchasolving | lol-cod | 2023-11-29T06:26:01Z | 0 | 0 | null | [
"keras",
"onnx",
"captcha",
"ocr",
"ai captcha solving",
"en",
"arxiv:1910.09700",
"license:unlicense",
"region:us"
] | 2023-11-29T06:26:01Z | 2023-11-29T06:02:19.000Z | null | null | ---
license: unlicense
language:
- en
library_name: keras
tags:
- captcha
- keras
- ocr
- ai captcha solving
---
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
This modelcard aims to be a base template for new models. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/modelcard_template.md?plain=1).
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
- **Developed by:** [Ashish Chaudhary aka lolcod]
- **Funded by [optional]:** [More Information Needed]
- **Shared by [optional]:** [More Information Needed]
- **Model type:** [More Information Needed]
- **Language(s) (NLP):** [More Information Needed]
- **License:** [More Information Needed]
- **Finetuned from model [optional]:** [More Information Needed]
### Model Sources [optional]
<!-- Provide the basic links for the model. -->
- **Repository:** [https://github.com/lol-cod/solvingcaptchakeras]
- **Paper [optional]:** [More Information Needed]
- **Demo [optional]:** [More Information Needed]
Direct Use
The model is designed for solving 4-lettered captchas with an 80% accuracy rate. It can be directly employed for captcha-solving tasks without the need for fine-tuning or integration into a larger ecosystem or application.
Downstream Use [optional]
[More Information Needed]
Out-of-Scope Use
The model is not intended for tasks beyond solving 4-lettered captchas. It may not perform well on captchas with a different format or on tasks unrelated to captcha-solving.
Bias, Risks, and Limitations
The model's performance may vary based on the complexity and variability of captchas. It may not generalize well to captchas with different characteristics or lengths. Additionally, there is a risk of misclassification, leading to incorrect solutions. The model might be sensitive to changes in background, font styles, or other captcha variations.
Recommendations
Users, both direct and downstream, should be aware of the model's limitations and potential biases. It is recommended to assess the performance on a diverse set of captchas to understand the model's capabilities and shortcomings.
How to Get Started with the Model
To use the model, you can leverage the following code:
python
Copy code
# Sample code for using the captcha-solving model
import keras
from keras.models import load_model
from captcha_solver import solve_captcha
# Load the pre-trained model
model = load_model('captcha_model.h5')
# Provide the captcha image as input
captcha_image = 'path/to/your/captcha.png'
solution = solve_captcha(model, captcha_image)
# Print the solution
print('Captcha Solution:', solution)
[More Information Needed]
Training Details
Training Data
The model was trained on a dataset of 4-lettered captchas. For more detailed information about the training data, refer to the accompanying Dataset Card.
[More Information Needed]
Training Procedure
Preprocessing [optional]
[More Information Needed]
Training Hyperparameters
Training regime: [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
[More Information Needed]
Speeds, Sizes, Times [optional]
[More Information Needed]
Evaluation
[More Information Needed]
<!-- This section describes the evaluation protocols and provides the results. -->
### Testing Data, Factors & Metrics
#### Testing Data
<!-- This should link to a Dataset Card if possible. -->
[More Information Needed]
#### Factors
<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
[More Information Needed]
#### Metrics
<!-- These are the evaluation metrics being used, ideally with a description of why. -->
[More Information Needed]
### Results
[More Information Needed]
#### Summary
## Model Examination [optional]
<!-- Relevant interpretability work for the model goes here -->
[More Information Needed]
## Environmental Impact
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
- **Hardware Type:** [More Information Needed]
- **Hours used:** [More Information Needed]
- **Cloud Provider:** [More Information Needed]
- **Compute Region:** [More Information Needed]
- **Carbon Emitted:** [More Information Needed]
## Technical Specifications [optional]
### Model Architecture and Objective
[More Information Needed]
### Compute Infrastructure
[More Information Needed]
#### Hardware
[More Information Needed]
#### Software
[More Information Needed]
## Citation [optional]
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
**BibTeX:**
[More Information Needed]
**APA:**
[More Information Needed]
## Glossary [optional]
<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
[More Information Needed]
## More Information [optional]
[More Information Needed]
## Model Card Authors [optional]
[More Information Needed]
## Model Card Contact
[More Information Needed]
| null | keras | null | null | null | null | null | null | null | null | null | null | lol-cod/captchasolving | [
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YuanXinwu/distil-bert-uncased-emotion-ft-1129 | YuanXinwu | 2023-11-29T06:26:01Z | 0 | 0 | null | [
"transformers",
"pytorch",
"distilbert",
"text-classification",
"endpoints_compatible",
"region:us"
] | 2023-11-29T06:26:01Z | 2023-11-29T06:02:50.000Z | null | null | Entry not found | null | transformers | text-classification | null | null | null | null | null | null | null | null | null | YuanXinwu/distil-bert-uncased-emotion-ft-1129 | [
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Zainab777/my_great_model | Zainab777 | 2023-11-29T06:16:53Z | 0 | 0 | null | [
"transformers",
"safetensors",
"distilbert",
"text-classification",
"generated_from_trainer",
"dataset:emotion",
"base_model:distilbert-base-uncased",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | 2023-11-29T06:16:53Z | 2023-11-29T06:07:49.000Z | null | null | ---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
datasets:
- emotion
model-index:
- name: my_great_model
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. -->
# my_great_model
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the emotion dataset.
## 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:
- learning_rate: 5e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
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teodor98/llama-Bulgarian-recepies | teodor98 | 2023-11-29T15:29:19Z | 0 | 0 | null | [
"transformers",
"safetensors",
"llama",
"text-generation",
"bg",
"license:llama2",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | 2023-11-29T15:29:19Z | 2023-11-29T06:08:20.000Z | null | null | ---
license: llama2
language:
- bg
---
This model is being trained with help of LORA technique on Bulgarian data from: https://www.kaggle.com/datasets/auhide/bulgarian-recipes-dataset/
This LLAMA version is 4bit encoded version of the 16bit LLAMA 2 7B model.
| null | transformers | text-generation | null | null | null | null | null | null | null | null | null | teodor98/llama-Bulgarian-recepies | [
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focean/relation-analysis | focean | 2023-11-29T06:09:01Z | 0 | 0 | null | [
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SanaFalakJ/results | SanaFalakJ | 2023-11-29T06:35:04Z | 0 | 0 | null | [
"tensorboard",
"generated_from_trainer",
"base_model:meta-llama/Llama-2-7b-chat-hf",
"region:us"
] | 2023-11-29T06:35:04Z | 2023-11-29T06:10:34.000Z | null | null | ---
base_model: meta-llama/Llama-2-7b-chat-hf
tags:
- generated_from_trainer
model-index:
- name: results
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. -->
# results
This model is a fine-tuned version of [meta-llama/Llama-2-7b-chat-hf](https://huggingface.co/meta-llama/Llama-2-7b-chat-hf) on an unknown dataset.
## 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:
- learning_rate: 0.0002
- train_batch_size: 2
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 1
### Training results
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
| null | null | null | null | null | null | null | null | null | null | null | null | SanaFalakJ/results | [
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BoB-KR/LDCC-GGUF | BoB-KR | 2023-11-29T06:17:51Z | 0 | 0 | null | [
"gguf",
"license:cc-by-4.0",
"region:us"
] | 2023-11-29T06:17:51Z | 2023-11-29T06:11:56.000Z | null | null | ---
license: cc-by-4.0
---
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saludobuenas/mistral7b | saludobuenas | 2023-11-29T06:12:03Z | 0 | 0 | null | [
"license:apache-2.0",
"region:us"
] | 2023-11-29T06:12:03Z | 2023-11-29T06:12:03.000Z | null | null | ---
license: apache-2.0
---
| null | null | null | null | null | null | null | null | null | null | null | null | saludobuenas/mistral7b | [
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YanweiLi/llama-vid-13b-full-224-video-fps-1 | YanweiLi | 2023-11-29T06:21:39Z | 0 | 0 | null | [
"transformers",
"pytorch",
"llava",
"text-generation",
"endpoints_compatible",
"region:us"
] | 2023-11-29T06:21:39Z | 2023-11-29T06:13:00.000Z | null | null | Entry not found | null | transformers | text-generation | null | null | null | null | null | null | null | null | null | YanweiLi/llama-vid-13b-full-224-video-fps-1 | [
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masterfury/checkpoints3 | masterfury | 2023-11-29T07:24:38Z | 0 | 0 | null | [
"region:us"
] | 2023-11-29T07:24:38Z | 2023-11-29T06:13:50.000Z | null | null | Entry not found | null | null | null | null | null | null | null | null | null | null | null | null | masterfury/checkpoints3 | [
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ameerazam08/sdxl_test_finetune | ameerazam08 | 2023-11-29T06:26:49Z | 0 | 0 | null | [
"region:us"
] | 2023-11-29T06:26:49Z | 2023-11-29T06:14:26.000Z | null | null | Entry not found | null | null | null | null | null | null | null | null | null | null | null | null | ameerazam08/sdxl_test_finetune | [
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crestf411/crestfall-nous-capybara-v1.9-yi-34b | crestf411 | 2023-11-29T06:33:21Z | 0 | 0 | null | [
"gguf",
"region:us"
] | 2023-11-29T06:33:21Z | 2023-11-29T06:17:19.000Z | null | null | Entry not found | null | null | null | null | null | null | null | null | null | null | null | null | crestf411/crestfall-nous-capybara-v1.9-yi-34b | [
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hkivancoral/hushem_5x_beit_base_rms_0001_fold2 | hkivancoral | 2023-11-29T06:49:03Z | 0 | 0 | null | [
"transformers",
"tensorboard",
"safetensors",
"beit",
"image-classification",
"generated_from_trainer",
"dataset:imagefolder",
"base_model:microsoft/beit-base-patch16-224",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | 2023-11-29T06:49:03Z | 2023-11-29T06:17:51.000Z | null | null | ---
license: apache-2.0
base_model: microsoft/beit-base-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: hushem_5x_beit_base_rms_0001_fold2
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: imagefolder
type: imagefolder
config: default
split: test
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.5111111111111111
---
<!-- 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. -->
# hushem_5x_beit_base_rms_0001_fold2
This model is a fine-tuned version of [microsoft/beit-base-patch16-224](https://huggingface.co/microsoft/beit-base-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 6.9592
- Accuracy: 0.5111
## 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:
- learning_rate: 0.0001
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 50
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.3984 | 1.0 | 27 | 1.3816 | 0.2889 |
| 1.3107 | 2.0 | 54 | 1.6609 | 0.2889 |
| 1.229 | 3.0 | 81 | 1.5449 | 0.2889 |
| 1.3814 | 4.0 | 108 | 1.6341 | 0.2889 |
| 1.2031 | 5.0 | 135 | 1.4184 | 0.2667 |
| 1.1619 | 6.0 | 162 | 1.4603 | 0.2889 |
| 1.1757 | 7.0 | 189 | 1.4200 | 0.2889 |
| 1.1575 | 8.0 | 216 | 1.3581 | 0.2889 |
| 1.0419 | 9.0 | 243 | 1.5164 | 0.4 |
| 1.0334 | 10.0 | 270 | 1.3939 | 0.4889 |
| 0.799 | 11.0 | 297 | 1.4216 | 0.5333 |
| 0.7589 | 12.0 | 324 | 1.5018 | 0.5111 |
| 0.7466 | 13.0 | 351 | 1.2714 | 0.3778 |
| 0.7077 | 14.0 | 378 | 1.2899 | 0.4 |
| 0.7022 | 15.0 | 405 | 1.4427 | 0.3333 |
| 0.6019 | 16.0 | 432 | 1.5793 | 0.4 |
| 0.6413 | 17.0 | 459 | 1.5251 | 0.3111 |
| 0.6003 | 18.0 | 486 | 2.0148 | 0.4889 |
| 0.5924 | 19.0 | 513 | 2.2670 | 0.4889 |
| 0.5357 | 20.0 | 540 | 2.0323 | 0.3556 |
| 0.5196 | 21.0 | 567 | 2.5285 | 0.4889 |
| 0.5137 | 22.0 | 594 | 3.7709 | 0.4222 |
| 0.4488 | 23.0 | 621 | 3.1001 | 0.5111 |
| 0.4667 | 24.0 | 648 | 2.9452 | 0.4 |
| 0.3277 | 25.0 | 675 | 2.8861 | 0.4667 |
| 0.3619 | 26.0 | 702 | 3.3939 | 0.5111 |
| 0.3379 | 27.0 | 729 | 3.5247 | 0.5333 |
| 0.2572 | 28.0 | 756 | 4.2104 | 0.5111 |
| 0.2257 | 29.0 | 783 | 3.4821 | 0.4889 |
| 0.2189 | 30.0 | 810 | 3.8860 | 0.4667 |
| 0.1431 | 31.0 | 837 | 5.2772 | 0.4667 |
| 0.2402 | 32.0 | 864 | 6.2470 | 0.4222 |
| 0.122 | 33.0 | 891 | 5.2693 | 0.4 |
| 0.2017 | 34.0 | 918 | 6.0732 | 0.5111 |
| 0.0844 | 35.0 | 945 | 6.0091 | 0.5556 |
| 0.1316 | 36.0 | 972 | 6.1584 | 0.4889 |
| 0.0377 | 37.0 | 999 | 7.3245 | 0.4889 |
| 0.1128 | 38.0 | 1026 | 6.6950 | 0.4444 |
| 0.0551 | 39.0 | 1053 | 7.0821 | 0.5111 |
| 0.0382 | 40.0 | 1080 | 7.5961 | 0.4889 |
| 0.0547 | 41.0 | 1107 | 6.2914 | 0.5111 |
| 0.0128 | 42.0 | 1134 | 6.4101 | 0.4889 |
| 0.0359 | 43.0 | 1161 | 6.6377 | 0.5111 |
| 0.004 | 44.0 | 1188 | 6.6707 | 0.4889 |
| 0.0224 | 45.0 | 1215 | 7.0078 | 0.4889 |
| 0.0292 | 46.0 | 1242 | 6.9800 | 0.4889 |
| 0.0156 | 47.0 | 1269 | 6.9010 | 0.4889 |
| 0.0096 | 48.0 | 1296 | 6.9583 | 0.5111 |
| 0.0108 | 49.0 | 1323 | 6.9592 | 0.5111 |
| 0.0394 | 50.0 | 1350 | 6.9592 | 0.5111 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
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JairamKanna/whisper-small.en-hi | JairamKanna | 2023-11-29T09:21:58Z | 0 | 0 | null | [
"transformers",
"tensorboard",
"safetensors",
"whisper",
"automatic-speech-recognition",
"endpoints_compatible",
"region:us"
] | 2023-11-29T09:21:58Z | 2023-11-29T06:18:12.000Z | null | null | Entry not found | null | transformers | automatic-speech-recognition | null | null | null | null | null | null | null | null | null | JairamKanna/whisper-small.en-hi | [
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irfnmaulaa/wsa2023 | irfnmaulaa | 2023-11-29T06:19:03Z | 0 | 0 | null | [
"license:mit",
"region:us"
] | 2023-11-29T06:19:03Z | 2023-11-29T06:19:03.000Z | null | null | ---
license: mit
---
| null | null | null | null | null | null | null | null | null | null | null | null | irfnmaulaa/wsa2023 | [
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brettbbb/finetune_mc_1 | brettbbb | 2023-11-29T06:22:18Z | 0 | 0 | null | [
"region:us"
] | 2023-11-29T06:22:18Z | 2023-11-29T06:22:17.000Z | null | null | Entry not found | null | null | null | null | null | null | null | null | null | null | null | null | brettbbb/finetune_mc_1 | [
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YanweiLi/llama-vid-13b-full-336 | YanweiLi | 2023-11-29T06:55:14Z | 0 | 0 | null | [
"transformers",
"pytorch",
"llava",
"text-generation",
"endpoints_compatible",
"region:us"
] | 2023-11-29T06:55:14Z | 2023-11-29T06:22:23.000Z | null | null | Entry not found | null | transformers | text-generation | null | null | null | null | null | null | null | null | null | YanweiLi/llama-vid-13b-full-336 | [
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Fay-zine/distilbert-sentiment-analysis | Fay-zine | 2023-11-29T07:17:23Z | 0 | 0 | null | [
"transformers",
"tensorboard",
"safetensors",
"distilbert",
"text-classification",
"endpoints_compatible",
"region:us"
] | 2023-11-29T07:17:23Z | 2023-11-29T06:23:13.000Z | null | null | Entry not found | null | transformers | text-classification | null | null | null | null | null | null | null | null | null | Fay-zine/distilbert-sentiment-analysis | [
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justswim/pstlllstrtns | justswim | 2023-11-29T06:23:39Z | 0 | 0 | null | [
"license:mit",
"region:us"
] | 2023-11-29T06:23:39Z | 2023-11-29T06:23:39.000Z | null | null | ---
license: mit
---
| null | null | null | null | null | null | null | null | null | null | null | null | justswim/pstlllstrtns | [
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Swayamjeet/SDXL_base_1 | Swayamjeet | 2023-11-29T08:11:01Z | 0 | 0 | null | [
"region:us"
] | 2023-11-29T08:11:01Z | 2023-11-29T06:24:19.000Z | null | null | Entry not found | null | null | null | null | null | null | null | null | null | null | null | null | Swayamjeet/SDXL_base_1 | [
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rechido/20231129_online_task1_batch64_epoch100 | rechido | 2023-11-29T07:06:04Z | 0 | 0 | null | [
"diffusers",
"diffusers:DDPMPipeline",
"region:us"
] | 2023-11-29T07:06:04Z | 2023-11-29T06:26:28.000Z | null | null | Entry not found | null | diffusers | null | null | null | null | null | null | null | null | null | null | rechido/20231129_online_task1_batch64_epoch100 | [
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rechido/20231129_online_task1_batch64_epoch200 | rechido | 2023-11-29T07:47:00Z | 0 | 0 | null | [
"diffusers",
"diffusers:DDPMPipeline",
"region:us"
] | 2023-11-29T07:47:00Z | 2023-11-29T06:26:52.000Z | null | null | Entry not found | null | diffusers | null | null | null | null | null | null | null | null | null | null | rechido/20231129_online_task1_batch64_epoch200 | [
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imdatta0/llama_2_13b_downproj_alpaca_r8_lr0.0001_bg8_upproj | imdatta0 | 2023-11-29T06:27:06Z | 0 | 0 | null | [
"generated_from_trainer",
"base_model:meta-llama/Llama-2-13b-hf",
"region:us"
] | 2023-11-29T06:27:06Z | 2023-11-29T06:27:03.000Z | null | null | ---
base_model: meta-llama/Llama-2-13b-hf
tags:
- generated_from_trainer
model-index:
- name: llama_2_13b_downproj_alpaca_r8_lr0.0001_bg8_upproj
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. -->
# llama_2_13b_downproj_alpaca_r8_lr0.0001_bg8_upproj
This model is a fine-tuned version of [meta-llama/Llama-2-13b-hf](https://huggingface.co/meta-llama/Llama-2-13b-hf) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7382
## 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:
- learning_rate: 0.0001
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 0.02
- num_epochs: 1
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.3769 | 0.01 | 33 | 0.9112 |
| 0.8976 | 0.02 | 66 | 0.8298 |
| 0.8279 | 0.03 | 99 | 0.7945 |
| 0.8053 | 0.04 | 132 | 0.7810 |
| 0.7828 | 0.05 | 165 | 0.7733 |
| 0.8198 | 0.06 | 198 | 0.7656 |
| 0.803 | 0.07 | 231 | 0.7609 |
| 0.774 | 0.08 | 264 | 0.7571 |
| 0.7887 | 0.09 | 297 | 0.7553 |
| 0.7804 | 0.1 | 330 | 0.7542 |
| 0.785 | 0.11 | 363 | 0.7528 |
| 0.7778 | 0.12 | 396 | 0.7521 |
| 0.7864 | 0.13 | 429 | 0.7506 |
| 0.7908 | 0.14 | 462 | 0.7505 |
| 0.7888 | 0.15 | 495 | 0.7498 |
| 0.7734 | 0.16 | 528 | 0.7490 |
| 0.7821 | 0.17 | 561 | 0.7485 |
| 0.7674 | 0.18 | 594 | 0.7484 |
| 0.7832 | 0.19 | 627 | 0.7478 |
| 0.7742 | 0.21 | 660 | 0.7483 |
| 0.7995 | 0.22 | 693 | 0.7473 |
| 0.7855 | 0.23 | 726 | 0.7479 |
| 0.7569 | 0.24 | 759 | 0.7458 |
| 0.7988 | 0.25 | 792 | 0.7472 |
| 0.7674 | 0.26 | 825 | 0.7452 |
| 0.7756 | 0.27 | 858 | 0.7449 |
| 0.7645 | 0.28 | 891 | 0.7457 |
| 0.7639 | 0.29 | 924 | 0.7451 |
| 0.7762 | 0.3 | 957 | 0.7445 |
| 0.7838 | 0.31 | 990 | 0.7432 |
| 0.7874 | 0.32 | 1023 | 0.7442 |
| 0.7788 | 0.33 | 1056 | 0.7441 |
| 0.7879 | 0.34 | 1089 | 0.7442 |
| 0.7823 | 0.35 | 1122 | 0.7442 |
| 0.7692 | 0.36 | 1155 | 0.7443 |
| 0.7704 | 0.37 | 1188 | 0.7428 |
| 0.7711 | 0.38 | 1221 | 0.7429 |
| 0.771 | 0.39 | 1254 | 0.7432 |
| 0.7538 | 0.4 | 1287 | 0.7421 |
| 0.7861 | 0.41 | 1320 | 0.7430 |
| 0.7819 | 0.42 | 1353 | 0.7423 |
| 0.7735 | 0.43 | 1386 | 0.7420 |
| 0.7742 | 0.44 | 1419 | 0.7419 |
| 0.765 | 0.45 | 1452 | 0.7414 |
| 0.7721 | 0.46 | 1485 | 0.7421 |
| 0.7695 | 0.47 | 1518 | 0.7426 |
| 0.7781 | 0.48 | 1551 | 0.7414 |
| 0.7667 | 0.49 | 1584 | 0.7412 |
| 0.7727 | 0.5 | 1617 | 0.7408 |
| 0.7802 | 0.51 | 1650 | 0.7406 |
| 0.7693 | 0.52 | 1683 | 0.7407 |
| 0.7616 | 0.53 | 1716 | 0.7404 |
| 0.7559 | 0.54 | 1749 | 0.7407 |
| 0.7487 | 0.55 | 1782 | 0.7404 |
| 0.7844 | 0.56 | 1815 | 0.7404 |
| 0.7522 | 0.57 | 1848 | 0.7405 |
| 0.7707 | 0.58 | 1881 | 0.7407 |
| 0.7834 | 0.59 | 1914 | 0.7400 |
| 0.7771 | 0.6 | 1947 | 0.7404 |
| 0.7775 | 0.62 | 1980 | 0.7409 |
| 0.7868 | 0.63 | 2013 | 0.7401 |
| 0.7584 | 0.64 | 2046 | 0.7402 |
| 0.7718 | 0.65 | 2079 | 0.7404 |
| 0.7658 | 0.66 | 2112 | 0.7399 |
| 0.7681 | 0.67 | 2145 | 0.7390 |
| 0.781 | 0.68 | 2178 | 0.7394 |
| 0.7629 | 0.69 | 2211 | 0.7397 |
| 0.7781 | 0.7 | 2244 | 0.7392 |
| 0.7735 | 0.71 | 2277 | 0.7390 |
| 0.7768 | 0.72 | 2310 | 0.7389 |
| 0.7632 | 0.73 | 2343 | 0.7389 |
| 0.7863 | 0.74 | 2376 | 0.7389 |
| 0.7687 | 0.75 | 2409 | 0.7387 |
| 0.795 | 0.76 | 2442 | 0.7394 |
| 0.7705 | 0.77 | 2475 | 0.7390 |
| 0.7733 | 0.78 | 2508 | 0.7391 |
| 0.7792 | 0.79 | 2541 | 0.7389 |
| 0.7615 | 0.8 | 2574 | 0.7386 |
| 0.7617 | 0.81 | 2607 | 0.7389 |
| 0.7752 | 0.82 | 2640 | 0.7389 |
| 0.7805 | 0.83 | 2673 | 0.7385 |
| 0.781 | 0.84 | 2706 | 0.7387 |
| 0.7387 | 0.85 | 2739 | 0.7386 |
| 0.7701 | 0.86 | 2772 | 0.7386 |
| 0.7746 | 0.87 | 2805 | 0.7385 |
| 0.7528 | 0.88 | 2838 | 0.7384 |
| 0.7902 | 0.89 | 2871 | 0.7384 |
| 0.7619 | 0.9 | 2904 | 0.7383 |
| 0.753 | 0.91 | 2937 | 0.7381 |
| 0.7779 | 0.92 | 2970 | 0.7381 |
| 0.7767 | 0.93 | 3003 | 0.7382 |
| 0.7694 | 0.94 | 3036 | 0.7382 |
| 0.7825 | 0.95 | 3069 | 0.7383 |
| 0.7665 | 0.96 | 3102 | 0.7382 |
| 0.7801 | 0.97 | 3135 | 0.7383 |
| 0.7687 | 0.98 | 3168 | 0.7383 |
| 0.7657 | 0.99 | 3201 | 0.7382 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.5.2
- Tokenizers 0.14.1
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Realgon/roberta_sst2_padding10model | Realgon | 2023-11-29T07:02:42Z | 0 | 0 | null | [
"transformers",
"pytorch",
"roberta",
"text-classification",
"generated_from_trainer",
"base_model:roberta-base",
"license:mit",
"endpoints_compatible",
"region:us"
] | 2023-11-29T07:02:42Z | 2023-11-29T06:27:41.000Z | null | null | ---
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: roberta_sst2_padding10model
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. -->
# roberta_sst2_padding10model
This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5439
- Accuracy: 0.9401
## 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:
- learning_rate: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log | 1.0 | 433 | 0.2015 | 0.9308 |
| 0.3269 | 2.0 | 866 | 0.3417 | 0.9083 |
| 0.1879 | 3.0 | 1299 | 0.2749 | 0.9357 |
| 0.109 | 4.0 | 1732 | 0.4100 | 0.9357 |
| 0.0667 | 5.0 | 2165 | 0.4702 | 0.9253 |
| 0.0426 | 6.0 | 2598 | 0.4966 | 0.9325 |
| 0.0255 | 7.0 | 3031 | 0.4133 | 0.9357 |
| 0.0255 | 8.0 | 3464 | 0.4515 | 0.9429 |
| 0.0222 | 9.0 | 3897 | 0.4046 | 0.9445 |
| 0.0278 | 10.0 | 4330 | 0.5288 | 0.9357 |
| 0.0119 | 11.0 | 4763 | 0.5001 | 0.9385 |
| 0.0085 | 12.0 | 5196 | 0.5208 | 0.9374 |
| 0.0138 | 13.0 | 5629 | 0.5213 | 0.9368 |
| 0.0097 | 14.0 | 6062 | 0.5023 | 0.9407 |
| 0.0097 | 15.0 | 6495 | 0.5428 | 0.9319 |
| 0.0111 | 16.0 | 6928 | 0.5067 | 0.9407 |
| 0.0041 | 17.0 | 7361 | 0.5007 | 0.9440 |
| 0.0053 | 18.0 | 7794 | 0.5224 | 0.9396 |
| 0.0009 | 19.0 | 8227 | 0.5436 | 0.9407 |
| 0.0019 | 20.0 | 8660 | 0.5439 | 0.9401 |
### Framework versions
- Transformers 4.32.1
- Pytorch 2.1.1
- Datasets 2.12.0
- Tokenizers 0.13.3
| null | transformers | text-classification | null | null | null | null | null | null | null | null | null | Realgon/roberta_sst2_padding10model | [
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kyle0518/HW3_r128 | kyle0518 | 2023-11-29T15:03:44Z | 0 | 0 | null | [
"generated_from_trainer",
"base_model:yentinglin/Taiwan-LLM-7B-v2.0-chat",
"license:apache-2.0",
"region:us"
] | 2023-11-29T15:03:44Z | 2023-11-29T06:29:47.000Z | null | null | ---
license: apache-2.0
base_model: yentinglin/Taiwan-LLM-7B-v2.0-chat
tags:
- generated_from_trainer
model-index:
- name: HW3_r128
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. -->
# HW3_r128
This model is a fine-tuned version of [yentinglin/Taiwan-LLM-7B-v2.0-chat](https://huggingface.co/yentinglin/Taiwan-LLM-7B-v2.0-chat) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0899
## 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:
- learning_rate: 0.0005
- train_batch_size: 2
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 32
- total_train_batch_size: 128
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 20
- num_epochs: 2
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.3456 | 0.3 | 20 | 1.2672 |
| 1.1827 | 0.6 | 40 | 1.1881 |
| 1.1513 | 0.9 | 60 | 1.1462 |
| 1.0925 | 1.2 | 80 | 1.1159 |
| 0.9697 | 1.51 | 100 | 1.1058 |
| 0.9442 | 1.81 | 120 | 1.0899 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.0.0
- Datasets 2.15.0
- Tokenizers 0.15.0
| null | null | null | null | null | null | null | null | null | null | null | null | kyle0518/HW3_r128 | [
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Firdho/Model | Firdho | 2023-11-29T06:31:46Z | 0 | 0 | null | [
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athirdpath/Iambe-20b-DARE | athirdpath | 2023-11-29T21:46:07Z | 0 | 2 | null | [
"transformers",
"safetensors",
"llama",
"text-generation",
"license:cc-by-nc-4.0",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | 2023-11-29T21:46:07Z | 2023-11-29T06:31:49.000Z | null | null | ---
license: cc-by-nc-4.0
---
<p align="center"><img src="https://i.ibb.co/pbpJHpk/iambe-sml.png"/><font size="6"> <b>Iambe-20b-DARE</b> </font></p>
## Description and Role
Named after a charming daughter of Echo and Pan in Greek myth, Iambe-20b-DARE is a [DARE](https://github.com/yule-BUAA/MergeLM) merge building on my recent experiments.
Iambe is intended to have the best realistically possible understanding of anatomy and of a scene's state for a 20b merge, while remaining personable and authentic in "voice".
## Prompting and Context
Iambe-20b-DARE uses Alpaca formatting, and has an effective context size of 4096 tokens. This model is uncensored, and the output/deployment of this model is the responsibility of the user.
## Method and Hypothesis
Based on my extended vanilla model [BigLlama](https://huggingface.co/athirdpath/BigLlama-20b), this adds elements of:
- [NeverSleep/Noromaid-20b-v0.1.1](https://huggingface.co/NeverSleep/Noromaid-20b-v0.1.1) - Addded to adapt the excellent writing and "soul" that come from the datasets backing this model.
- [athirdpath/Eileithyia-20b](https://huggingface.co/athirdpath/Eileithyia-20b) - Added at low weight and density to capture anatomical data and its relation to fiction without the model's other... quirks.
- [athirdpath/CleverGirl-20b-Blended](https://huggingface.co/athirdpath/CleverGirl-20b-Blended) - Added to capture CleverGirl's problem-solving abilities.
<p align="center"><font size="7"> <b>Examples</b></font>
<p align="center"><font size="3"> <i>(q5_k_m GGUF quant, Ooba textgen, Midnight Enigma preset for KISS reasons)</i></font>
<p align="center"><font size="5"> Reasoning and Recall - STEM</font><img src="https://i.ibb.co/YDkRD43/base.png"/>
<p align="center"><font size="5"> Reasoning and Recall - Social Science</font><img src="https://i.ibb.co/L0kc3pb/Screenshot-2023-11-29-024037.png"/>
<p align="center"><font size="5"> Ethics and Prompt Interpretation</font><img src="https://i.ibb.co/b5vH6jD/Screenshot-2023-11-29-040408.png"/>
<p align="center"><font size="5">Role-Playing, Complex Card</font>
<p align="center"><font size="3">SillyTavern, Roleplay instruct preset, just Min_P 0.1 and Temp 1.2</font><img src="https://i.ibb.co/NrKNn2j/Screenshot-2023-11-29-051923.png"/>
<p align="center"><font size="6"><b><a href="https://i.ibb.co/m5G0ZVp/Screenshot-2023-11-29-004705.png">!!NSFW!! - Erotica Writing Example - !!NSFW!!</font></a></b></p>
## Testing and Conclusions
VERY Impressed so far, concrete data coming eventually.
Does still have some confusion (at q5_k_m), but has instantly become my daily driver.
## Recipe
merge_method: dare_ties
- base_model: athirdpath/BigLlama-20b
- model: NeverSleep/Noromaid-20b-v0.1.1
weight: 0.41 / density: 0.50
- model: athirdpath/Eileithyia-20b
weight: 0.18 / density: 0.30
- model: athirdpath/CleverGirl-20b-Blended
weight: 0.41 / density: 0.50
int8_mask: true
dtype: bfloat16
## Gratitude
Thanks to brucethemoose for the recipe. Thanks to Undi95 and IkariDev at NeverSleep for Noromaid, as well as lots of inspiration. Thanks to Sao10K for [half of](https://huggingface.co/Sao10K/Mythical-Destroyer-V2-L2-13B) CleverGirl.
## Geneology Credits - Models and LoRAs, 3 levels deep
- athirdpath/BigLlama-20b
- TheBloke/Llama-2-13B-fp16
- iamshnoo/alpaca-2-13b-english
- NeverSleep/Noromaid-20b-v0.1.1
- Aesir Private RP dataset
- HuggingFaceH4/no_robots
- athirdpath/CleverGirl-20b-Blended
- athirdpath/Orca-2-13b-Alpaca-Uncensored
- microsoft/Orca-2-13b
- athirdpath/Orca-2-13b-Alpaca-Uncensored-LORA
- Sao10K/Mythical-Destroyer-V2-L2-13B
- TheBloke/Llama-2-13B-fp16
- Gryphe/MythoMax-L2-13b
- totally-not-an-llm/PuddleJumper-13b
- jondurbin/airoboros-l2-13b-2.1
- rombodawg/LosslessMegaCoder-llama2-13b-mini
- The-Face-Of-Goonery/Chronos-Beluga-v2-13bfp16
- athirdpath/Eileithyia-20b
- athirdpath/Harmonia-20B
- Undi95/Emerhyst-20B
- Undi95/Emerald-13B
- Undi95/Amethyst-13B
- Undi95/MXLewd-L2-20B
- Undi95/MLewd-L2-13B-v2-3
- Undi95/ReMM-v2.1-L2-13B
- Xwin-LM/Xwin-LM-13B-V0.1
- Undi95/Lewd-Sydney-20B
- Free_Sydney_V2_13b_HF
- Undi95/Xwin-MLewd-13B-V0.2
- lemonilia/LimaRP-Llama2-13B-v3-EXPERIMENT
- athirdpath/Nethena-20b-Glued
- NeverSleep/Nethena-20B
- athirdpath/Nethena-20b-Glue-LORA
- tavtav/Rose-20B
- CalderaAI/13B-Thorns-l2
- NeverSleep/Noromaid-13b-v0.1.0
- Undi95/PsyMedRP-v1-20B
- jondurbin/airoboros-l2-13b-3.0
- ehartford/Samantha-1.11-13b
- Xwin-LM/Xwin-LM-13B-V0.1
- chaoyi-wu/MedLLaMA_13B
- migtissera/Synthia-13B-v1.2
- NeverSleep/Noromaid-20b-v0.1.1
- Aesir Private RP dataset
- HuggingFaceH4/no_robots
- Undi95/U-Amethyst-20B
- Xwin-LM/Xwin-LM-13B-V0.1
- The-Face-Of-Goonery/Huginn-13b-FP16
- zattio770/120-Days-of-LORA-v2-13B
- lemonilia/LimaRP-Llama2-13B-v3-EXPERIMENT
- Undi95/Unholy-v1-12L-13B
- athirdpath/Eileithyia-20b-LORA
Thanks again to everyone involved. | null | transformers | text-generation | null | null | null | null | null | null | null | null | null | athirdpath/Iambe-20b-DARE | [
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heartpawit/textual_inversion_cat | heartpawit | 2023-11-29T06:32:26Z | 0 | 0 | null | [
"region:us"
] | 2023-11-29T06:32:26Z | 2023-11-29T06:32:26.000Z | null | null | Entry not found | null | null | null | null | null | null | null | null | null | null | null | null | heartpawit/textual_inversion_cat | [
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panwoo00/LE_project2 | panwoo00 | 2023-11-29T06:41:55Z | 0 | 0 | null | [
"transformers",
"pytorch",
"llama",
"text-generation",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | 2023-11-29T06:41:55Z | 2023-11-29T06:32:38.000Z | null | null | Entry not found | null | transformers | text-generation | null | null | null | null | null | null | null | null | null | panwoo00/LE_project2 | [
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bluepen5805/blue_pencil-XL-Turbo | bluepen5805 | 2023-11-29T07:18:16Z | 0 | 0 | null | [
"license:other",
"region:us"
] | 2023-11-29T07:18:16Z | 2023-11-29T06:33:15.000Z | null | null | ---
license: other
license_name: stability-ai-non-commercial-research-community-license
license_link: https://huggingface.co/stabilityai/sdxl-turbo/blob/main/LICENSE.TXT
---
# LICENSE: [STABILITY AI NON-COMMERCIAL RESEARCH COMMUNITY LICENSE](https://huggingface.co/stabilityai/sdxl-turbo/blob/main/LICENSE.TXT)
試しに作ってみただけです。 | null | null | null | null | null | null | null | null | null | null | null | null | bluepen5805/blue_pencil-XL-Turbo | [
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afrideva/malaysian-mistral-1.1B-4096-GGUF | afrideva | 2023-11-29T06:44:19Z | 0 | 0 | null | [
"gguf",
"ggml",
"quantized",
"q2_k",
"q3_k_m",
"q4_k_m",
"q5_k_m",
"q6_k",
"q8_0",
"text-generation",
"ms",
"base_model:mesolitica/malaysian-mistral-1.1B-4096",
"region:us"
] | 2023-11-29T06:44:19Z | 2023-11-29T06:34:22.000Z | null | null | ---
base_model: mesolitica/malaysian-mistral-1.1B-4096
inference: false
language:
- ms
model_creator: mesolitica
model_name: malaysian-mistral-1.1B-4096
pipeline_tag: text-generation
quantized_by: afrideva
tags:
- gguf
- ggml
- quantized
- q2_k
- q3_k_m
- q4_k_m
- q5_k_m
- q6_k
- q8_0
---
# mesolitica/malaysian-mistral-1.1B-4096-GGUF
Quantized GGUF model files for [malaysian-mistral-1.1B-4096](https://huggingface.co/mesolitica/malaysian-mistral-1.1B-4096) from [mesolitica](https://huggingface.co/mesolitica)
| Name | Quant method | Size |
| ---- | ---- | ---- |
| [malaysian-mistral-1.1b-4096.fp16.gguf](https://huggingface.co/afrideva/malaysian-mistral-1.1B-4096-GGUF/resolve/main/malaysian-mistral-1.1b-4096.fp16.gguf) | fp16 | 2.25 GB |
| [malaysian-mistral-1.1b-4096.q2_k.gguf](https://huggingface.co/afrideva/malaysian-mistral-1.1B-4096-GGUF/resolve/main/malaysian-mistral-1.1b-4096.q2_k.gguf) | q2_k | 491.42 MB |
| [malaysian-mistral-1.1b-4096.q3_k_m.gguf](https://huggingface.co/afrideva/malaysian-mistral-1.1B-4096-GGUF/resolve/main/malaysian-mistral-1.1b-4096.q3_k_m.gguf) | q3_k_m | 561.96 MB |
| [malaysian-mistral-1.1b-4096.q4_k_m.gguf](https://huggingface.co/afrideva/malaysian-mistral-1.1B-4096-GGUF/resolve/main/malaysian-mistral-1.1b-4096.q4_k_m.gguf) | q4_k_m | 682.68 MB |
| [malaysian-mistral-1.1b-4096.q5_k_m.gguf](https://huggingface.co/afrideva/malaysian-mistral-1.1B-4096-GGUF/resolve/main/malaysian-mistral-1.1b-4096.q5_k_m.gguf) | q5_k_m | 799.13 MB |
| [malaysian-mistral-1.1b-4096.q6_k.gguf](https://huggingface.co/afrideva/malaysian-mistral-1.1B-4096-GGUF/resolve/main/malaysian-mistral-1.1b-4096.q6_k.gguf) | q6_k | 922.87 MB |
| [malaysian-mistral-1.1b-4096.q8_0.gguf](https://huggingface.co/afrideva/malaysian-mistral-1.1B-4096-GGUF/resolve/main/malaysian-mistral-1.1b-4096.q8_0.gguf) | q8_0 | 1.19 GB |
## Original Model Card:
# Pretrain 1.1B 4096 context length Mistral on Malaysian text
README at https://github.com/mesolitica/malaya/tree/5.1/pretrained-model/mistral
- Dataset gathered at https://github.com/malaysia-ai/dedup-text-dataset/tree/main/pretrain-llm
- We use Ray cluster to train on 5 nodes of 4x A100 80GB, https://github.com/malaysia-ai/jupyter-gpu/tree/main/ray
WandB, https://wandb.ai/mesolitica/pretrain-mistral-1.1b?workspace=user-husein-mesolitica
WandB report, https://wandb.ai/mesolitica/pretrain-mistral-3b/reports/Pretrain-Larger-Malaysian-Mistral--Vmlldzo2MDkyOTgz
## how-to
```python
from transformers import AutoTokenizer, AutoModelForCausalLM, BitsAndBytesConfig
import torch
TORCH_DTYPE = 'bfloat16'
nf4_config = BitsAndBytesConfig(
load_in_4bit=True,
bnb_4bit_quant_type='nf4',
bnb_4bit_use_double_quant=True,
bnb_4bit_compute_dtype=getattr(torch, TORCH_DTYPE)
)
tokenizer = AutoTokenizer.from_pretrained('mesolitica/malaysian-mistral-1.1B-4096', model_input_names = ['input_ids'])
model = AutoModelForCausalLM.from_pretrained(
'mesolitica/malaysian-mistral-1.1B-4096',
use_flash_attention_2 = True,
quantization_config = nf4_config
)
prompt = '<s>nama saya'
inputs = tokenizer([prompt], return_tensors='pt', add_special_tokens=False).to('cuda')
generate_kwargs = dict(
inputs,
max_new_tokens=512,
top_p=0.95,
top_k=50,
temperature=0.9,
do_sample=True,
num_beams=1,
repetition_penalty=1.05,
)
r = model.generate(**generate_kwargs)
``` | null | null | text-generation | null | null | null | null | null | null | null | null | null | afrideva/malaysian-mistral-1.1B-4096-GGUF | [
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bryanzhang24/albert-base-v2-finetuned | bryanzhang24 | 2023-11-29T06:34:44Z | 0 | 0 | null | [
"region:us"
] | 2023-11-29T06:34:44Z | 2023-11-29T06:34:44.000Z | null | null | Entry not found | null | null | null | null | null | null | null | null | null | null | null | null | bryanzhang24/albert-base-v2-finetuned | [
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againeureka/my_awesome_swag_model | againeureka | 2023-11-29T06:36:03Z | 0 | 0 | null | [
"region:us"
] | 2023-11-29T06:36:03Z | 2023-11-29T06:36:03.000Z | null | null | Entry not found | null | null | null | null | null | null | null | null | null | null | null | null | againeureka/my_awesome_swag_model | [
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AKKi-028/wireframe | AKKi-028 | 2023-11-29T06:39:41Z | 0 | 0 | null | [
"region:us"
] | 2023-11-29T06:39:41Z | 2023-11-29T06:39:41.000Z | null | null | Entry not found | null | null | null | null | null | null | null | null | null | null | null | null | AKKi-028/wireframe | [
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mdosama39/xlm-roberta-base-FakeNews-Dravidian-LR | mdosama39 | 2023-11-29T06:43:12Z | 0 | 0 | null | [
"region:us"
] | 2023-11-29T06:43:12Z | 2023-11-29T06:43:11.000Z | null | null | Entry not found | null | null | null | null | null | null | null | null | null | null | null | null | mdosama39/xlm-roberta-base-FakeNews-Dravidian-LR | [
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Anant58/ReinforceCartpoleV1 | Anant58 | 2023-11-29T06:45:15Z | 0 | 0 | null | [
"CartPole-v1",
"reinforce",
"reinforcement-learning",
"custom-implementation",
"deep-rl-class",
"model-index",
"region:us"
] | 2023-11-29T06:45:15Z | 2023-11-29T06:45:04.000Z | null | null | ---
tags:
- CartPole-v1
- reinforce
- reinforcement-learning
- custom-implementation
- deep-rl-class
model-index:
- name: ReinforceCartpoleV1
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: CartPole-v1
type: CartPole-v1
metrics:
- type: mean_reward
value: 500.00 +/- 0.00
name: mean_reward
verified: false
---
# **Reinforce** Agent playing **CartPole-v1**
This is a trained model of a **Reinforce** agent playing **CartPole-v1** .
To learn to use this model and train yours check Unit 4 of the Deep Reinforcement Learning Course: https://huggingface.co/deep-rl-course/unit4/introduction
| null | null | reinforcement-learning | null | null | null | null | null | null | null | null | null | Anant58/ReinforceCartpoleV1 | [
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renjua/Test_SrNo_40_v1 | renjua | 2023-11-29T06:45:50Z | 0 | 0 | null | [
"region:us"
] | 2023-11-29T06:45:50Z | 2023-11-29T06:45:48.000Z | null | null | Entry not found | null | null | null | null | null | null | null | null | null | null | null | null | renjua/Test_SrNo_40_v1 | [
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hyonbokan/llama_5G_analysis_5kEpoch | hyonbokan | 2023-11-29T06:55:26Z | 0 | 0 | null | [
"transformers",
"pytorch",
"llama",
"text-generation",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | 2023-11-29T06:55:26Z | 2023-11-29T06:47:07.000Z | null | null | Entry not found | null | transformers | text-generation | null | null | null | null | null | null | null | null | null | hyonbokan/llama_5G_analysis_5kEpoch | [
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hkivancoral/hushem_5x_beit_base_rms_0001_fold3 | hkivancoral | 2023-11-29T07:21:47Z | 0 | 0 | null | [
"transformers",
"tensorboard",
"safetensors",
"beit",
"image-classification",
"generated_from_trainer",
"dataset:imagefolder",
"base_model:microsoft/beit-base-patch16-224",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | 2023-11-29T07:21:47Z | 2023-11-29T06:49:53.000Z | null | null | ---
license: apache-2.0
base_model: microsoft/beit-base-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: hushem_5x_beit_base_rms_0001_fold3
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: imagefolder
type: imagefolder
config: default
split: test
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.6744186046511628
---
<!-- 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. -->
# hushem_5x_beit_base_rms_0001_fold3
This model is a fine-tuned version of [microsoft/beit-base-patch16-224](https://huggingface.co/microsoft/beit-base-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 2.0271
- Accuracy: 0.6744
## 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:
- learning_rate: 0.0001
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 50
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.4187 | 1.0 | 28 | 1.4291 | 0.2558 |
| 1.401 | 2.0 | 56 | 1.4569 | 0.2558 |
| 1.367 | 3.0 | 84 | 1.2989 | 0.2791 |
| 1.3068 | 4.0 | 112 | 1.1706 | 0.5116 |
| 1.282 | 5.0 | 140 | 1.1869 | 0.5581 |
| 1.1177 | 6.0 | 168 | 0.8916 | 0.7442 |
| 0.8904 | 7.0 | 196 | 0.7798 | 0.7209 |
| 0.9449 | 8.0 | 224 | 0.6587 | 0.7674 |
| 0.8708 | 9.0 | 252 | 1.0524 | 0.5814 |
| 0.9352 | 10.0 | 280 | 0.7664 | 0.6744 |
| 0.8718 | 11.0 | 308 | 0.6191 | 0.7907 |
| 0.7977 | 12.0 | 336 | 1.1991 | 0.6512 |
| 0.8081 | 13.0 | 364 | 0.7062 | 0.7674 |
| 0.7399 | 14.0 | 392 | 0.7130 | 0.6744 |
| 0.8202 | 15.0 | 420 | 0.7484 | 0.6977 |
| 0.7069 | 16.0 | 448 | 0.6665 | 0.6977 |
| 0.6169 | 17.0 | 476 | 0.7828 | 0.6279 |
| 0.6766 | 18.0 | 504 | 0.9849 | 0.5814 |
| 0.6876 | 19.0 | 532 | 0.7015 | 0.7442 |
| 0.5123 | 20.0 | 560 | 0.9230 | 0.7442 |
| 0.4885 | 21.0 | 588 | 0.9671 | 0.6279 |
| 0.5212 | 22.0 | 616 | 1.2712 | 0.6744 |
| 0.5047 | 23.0 | 644 | 0.7902 | 0.6512 |
| 0.4047 | 24.0 | 672 | 1.3996 | 0.7209 |
| 0.361 | 25.0 | 700 | 1.1508 | 0.6279 |
| 0.362 | 26.0 | 728 | 1.0709 | 0.6279 |
| 0.3752 | 27.0 | 756 | 0.9894 | 0.6512 |
| 0.2958 | 28.0 | 784 | 1.2219 | 0.6279 |
| 0.3016 | 29.0 | 812 | 0.8154 | 0.6977 |
| 0.2083 | 30.0 | 840 | 1.2432 | 0.6047 |
| 0.2249 | 31.0 | 868 | 1.5401 | 0.6047 |
| 0.1443 | 32.0 | 896 | 1.3193 | 0.6279 |
| 0.1501 | 33.0 | 924 | 1.1707 | 0.6977 |
| 0.1715 | 34.0 | 952 | 1.1677 | 0.7442 |
| 0.2795 | 35.0 | 980 | 1.2992 | 0.6744 |
| 0.1174 | 36.0 | 1008 | 1.6643 | 0.6744 |
| 0.1132 | 37.0 | 1036 | 1.7522 | 0.6279 |
| 0.0738 | 38.0 | 1064 | 1.6182 | 0.6744 |
| 0.0433 | 39.0 | 1092 | 2.1223 | 0.6512 |
| 0.0483 | 40.0 | 1120 | 2.5522 | 0.5814 |
| 0.0333 | 41.0 | 1148 | 1.8374 | 0.6977 |
| 0.0107 | 42.0 | 1176 | 1.9629 | 0.6744 |
| 0.013 | 43.0 | 1204 | 1.6900 | 0.7209 |
| 0.0316 | 44.0 | 1232 | 2.1881 | 0.6512 |
| 0.0272 | 45.0 | 1260 | 1.8428 | 0.6744 |
| 0.0298 | 46.0 | 1288 | 1.7049 | 0.7674 |
| 0.0196 | 47.0 | 1316 | 1.9117 | 0.6744 |
| 0.0084 | 48.0 | 1344 | 2.0336 | 0.6744 |
| 0.0059 | 49.0 | 1372 | 2.0271 | 0.6744 |
| 0.0065 | 50.0 | 1400 | 2.0271 | 0.6744 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
| null | transformers | image-classification | null | null | null | null | null | null | null | null | null | hkivancoral/hushem_5x_beit_base_rms_0001_fold3 | [
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sheduele/mbert_ver_2_task_1A | sheduele | 2023-11-29T08:34:55Z | 0 | 0 | null | [
"transformers",
"pytorch",
"tensorboard",
"bert",
"text-classification",
"generated_from_trainer",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | 2023-11-29T08:34:55Z | 2023-11-29T06:50:35.000Z | null | null | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: mbert_ver_2_task_1A
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. -->
# mbert_ver_2_task_1A
This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3826
- Accuracy: 0.9003
- F1: 0.8999
- Precision: 0.8998
- Recall: 0.9003
## 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:
- learning_rate: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.2827 | 1.0 | 3523 | 0.2734 | 0.8841 | 0.8826 | 0.8921 | 0.8841 |
| 0.2242 | 2.0 | 7046 | 0.2799 | 0.8949 | 0.8957 | 0.8972 | 0.8949 |
| 0.1658 | 3.0 | 10569 | 0.3093 | 0.9003 | 0.9000 | 0.9004 | 0.9003 |
| 0.1404 | 4.0 | 14092 | 0.3826 | 0.9003 | 0.8999 | 0.8998 | 0.9003 |
### Framework versions
- Transformers 4.30.1
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3
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Vinayak7/Health_GPT | Vinayak7 | 2023-11-29T06:51:27Z | 0 | 0 | null | [
"region:us"
] | 2023-11-29T06:51:27Z | 2023-11-29T06:51:27.000Z | null | null | Entry not found | null | null | null | null | null | null | null | null | null | null | null | null | Vinayak7/Health_GPT | [
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boohboohdog/Gemma | boohboohdog | 2023-11-29T06:54:13Z | 0 | 0 | null | [
"license:mit",
"region:us"
] | 2023-11-29T06:54:13Z | 2023-11-29T06:54:13.000Z | null | null | ---
license: mit
---
| null | null | null | null | null | null | null | null | null | null | null | null | boohboohdog/Gemma | [
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Spacyzipa/todayModel | Spacyzipa | 2023-11-29T07:05:22Z | 0 | 0 | null | [
"transformers",
"safetensors",
"vision-encoder-decoder",
"endpoints_compatible",
"region:us"
] | 2023-11-29T07:05:22Z | 2023-11-29T06:54:19.000Z | null | null | Entry not found | null | transformers | null | null | null | null | null | null | null | null | null | null | Spacyzipa/todayModel | [
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adamjweintraut/bart-finetuned-eli5_lfqa_top | adamjweintraut | 2023-11-29T10:22:45Z | 0 | 0 | null | [
"transformers",
"tensorboard",
"safetensors",
"bart",
"text2text-generation",
"generated_from_trainer",
"base_model:facebook/bart-large",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | 2023-11-29T10:22:45Z | 2023-11-29T06:54:28.000Z | null | null | ---
license: apache-2.0
base_model: facebook/bart-large
tags:
- generated_from_trainer
model-index:
- name: bart-finetuned-eli5_lfqa_top
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. -->
# bart-finetuned-eli5_lfqa_top
This model is a fine-tuned version of [facebook/bart-large](https://huggingface.co/facebook/bart-large) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.8504
## 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:
- learning_rate: 5e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 1.8025 | 1.0 | 10004 | 1.8504 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
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Jan4ik181/produkt | Jan4ik181 | 2023-11-29T06:58:46Z | 0 | 0 | null | [
"region:us"
] | 2023-11-29T06:58:46Z | 2023-11-29T06:58:46.000Z | null | null | Entry not found | null | null | null | null | null | null | null | null | null | null | null | null | Jan4ik181/produkt | [
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Tippawan/old-thainer-version | Tippawan | 2023-11-29T06:59:29Z | 0 | 0 | null | [
"transformers",
"safetensors",
"camembert",
"token-classification",
"ner",
"generated_from_trainer",
"base_model:pythainlp/thainer-corpus-v2-base-model",
"license:cc-by-4.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | 2023-11-29T06:59:29Z | 2023-11-29T06:58:50.000Z | null | null | ---
license: cc-by-4.0
base_model: pythainlp/thainer-corpus-v2-base-model
tags:
- ner
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: thainer_corpus_v2_model
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. -->
# thainer_corpus_v2_model
This model is a fine-tuned version of [pythainlp/thainer-corpus-v2-base-model](https://huggingface.co/pythainlp/thainer-corpus-v2-base-model) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1426
- Precision: 0.7086
- Recall: 0.7514
- F1: 0.7294
- Accuracy: 0.9509
## 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:
- learning_rate: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.1969 | 1.0 | 792 | 0.1844 | 0.6572 | 0.7524 | 0.7016 | 0.9409 |
| 0.1238 | 2.0 | 1584 | 0.1705 | 0.7069 | 0.7676 | 0.7360 | 0.9463 |
| 0.1078 | 3.0 | 2376 | 0.1689 | 0.7096 | 0.7671 | 0.7372 | 0.9466 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
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Realgon/roberta_sst2_padding20model | Realgon | 2023-11-29T07:46:29Z | 0 | 0 | null | [
"transformers",
"pytorch",
"roberta",
"text-classification",
"generated_from_trainer",
"base_model:roberta-base",
"license:mit",
"endpoints_compatible",
"region:us"
] | 2023-11-29T07:46:29Z | 2023-11-29T07:02:46.000Z | null | null | ---
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: roberta_sst2_padding20model
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. -->
# roberta_sst2_padding20model
This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6078
- Accuracy: 0.9352
## 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:
- learning_rate: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log | 1.0 | 433 | 0.1998 | 0.9308 |
| 0.3269 | 2.0 | 866 | 0.2333 | 0.9314 |
| 0.2012 | 3.0 | 1299 | 0.3003 | 0.9396 |
| 0.1167 | 4.0 | 1732 | 0.3685 | 0.9341 |
| 0.0788 | 5.0 | 2165 | 0.4704 | 0.9270 |
| 0.0356 | 6.0 | 2598 | 0.3796 | 0.9374 |
| 0.0394 | 7.0 | 3031 | 0.5460 | 0.9303 |
| 0.0394 | 8.0 | 3464 | 0.5014 | 0.9303 |
| 0.026 | 9.0 | 3897 | 0.6623 | 0.9023 |
| 0.024 | 10.0 | 4330 | 0.4954 | 0.9264 |
| 0.0206 | 11.0 | 4763 | 0.4857 | 0.9363 |
| 0.0107 | 12.0 | 5196 | 0.5563 | 0.9341 |
| 0.0123 | 13.0 | 5629 | 0.5101 | 0.9368 |
| 0.0089 | 14.0 | 6062 | 0.5152 | 0.9396 |
| 0.0089 | 15.0 | 6495 | 0.5144 | 0.9407 |
| 0.0083 | 16.0 | 6928 | 0.5447 | 0.9363 |
| 0.0057 | 17.0 | 7361 | 0.5785 | 0.9341 |
| 0.0039 | 18.0 | 7794 | 0.6073 | 0.9363 |
| 0.003 | 19.0 | 8227 | 0.5985 | 0.9357 |
| 0.003 | 20.0 | 8660 | 0.6078 | 0.9352 |
### Framework versions
- Transformers 4.32.1
- Pytorch 2.1.1
- Datasets 2.12.0
- Tokenizers 0.13.3
| null | transformers | text-classification | null | null | null | null | null | null | null | null | null | Realgon/roberta_sst2_padding20model | [
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knnkrt/Realistic-Vision-V5.1-Inpainting | knnkrt | 2023-11-29T07:52:58Z | 0 | 0 | null | [
"license:creativeml-openrail-m",
"region:us"
] | 2023-11-29T07:52:58Z | 2023-11-29T07:04:20.000Z | null | null | ---
license: creativeml-openrail-m
---
| null | null | null | null | null | null | null | null | null | null | null | null | knnkrt/Realistic-Vision-V5.1-Inpainting | [
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develonur/realistic_vision_v5.1_vae_inpainting | develonur | 2023-11-29T07:12:58Z | 0 | 0 | null | [
"license:creativeml-openrail-m",
"region:us"
] | 2023-11-29T07:12:58Z | 2023-11-29T07:05:26.000Z | null | null | ---
license: creativeml-openrail-m
---
| null | null | null | null | null | null | null | null | null | null | null | null | develonur/realistic_vision_v5.1_vae_inpainting | [
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onizukal/SMIDS_10x_beit_base_adamax_lr00001_fold4 | onizukal | 2023-11-29T10:59:45Z | 0 | 0 | null | [
"transformers",
"safetensors",
"beit",
"image-classification",
"generated_from_trainer",
"dataset:imagefolder",
"base_model:microsoft/beit-base-patch16-224",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | 2023-11-29T10:59:45Z | 2023-11-29T07:06:01.000Z | null | null | ---
license: apache-2.0
base_model: microsoft/beit-base-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: SMIDS_10x_beit_base_adamax_lr00001_fold4
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: imagefolder
type: imagefolder
config: default
split: test
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.905
---
<!-- 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. -->
# SMIDS_10x_beit_base_adamax_lr00001_fold4
This model is a fine-tuned version of [microsoft/beit-base-patch16-224](https://huggingface.co/microsoft/beit-base-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0909
- Accuracy: 0.905
## 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:
- learning_rate: 1e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 50
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.205 | 1.0 | 750 | 0.3272 | 0.875 |
| 0.1515 | 2.0 | 1500 | 0.3394 | 0.8867 |
| 0.085 | 3.0 | 2250 | 0.3691 | 0.885 |
| 0.0852 | 4.0 | 3000 | 0.4431 | 0.8783 |
| 0.0574 | 5.0 | 3750 | 0.5163 | 0.8833 |
| 0.0273 | 6.0 | 4500 | 0.5611 | 0.89 |
| 0.0295 | 7.0 | 5250 | 0.6607 | 0.8883 |
| 0.0155 | 8.0 | 6000 | 0.6978 | 0.89 |
| 0.0038 | 9.0 | 6750 | 0.7174 | 0.8917 |
| 0.0099 | 10.0 | 7500 | 0.7725 | 0.9 |
| 0.0007 | 11.0 | 8250 | 0.8430 | 0.8933 |
| 0.0003 | 12.0 | 9000 | 0.8762 | 0.895 |
| 0.0085 | 13.0 | 9750 | 0.8261 | 0.8883 |
| 0.0017 | 14.0 | 10500 | 0.9148 | 0.8933 |
| 0.0247 | 15.0 | 11250 | 0.9919 | 0.8917 |
| 0.0636 | 16.0 | 12000 | 0.9588 | 0.895 |
| 0.0017 | 17.0 | 12750 | 0.9715 | 0.8983 |
| 0.0002 | 18.0 | 13500 | 0.9401 | 0.8917 |
| 0.0 | 19.0 | 14250 | 0.9913 | 0.8967 |
| 0.0018 | 20.0 | 15000 | 0.9533 | 0.9033 |
| 0.0008 | 21.0 | 15750 | 0.9742 | 0.91 |
| 0.0007 | 22.0 | 16500 | 1.0396 | 0.9 |
| 0.0003 | 23.0 | 17250 | 1.0350 | 0.9017 |
| 0.0143 | 24.0 | 18000 | 1.0024 | 0.895 |
| 0.0001 | 25.0 | 18750 | 1.0257 | 0.895 |
| 0.0001 | 26.0 | 19500 | 1.0174 | 0.8967 |
| 0.0002 | 27.0 | 20250 | 1.0224 | 0.8983 |
| 0.0001 | 28.0 | 21000 | 1.0572 | 0.8933 |
| 0.0034 | 29.0 | 21750 | 1.0487 | 0.8933 |
| 0.0058 | 30.0 | 22500 | 1.0703 | 0.8917 |
| 0.0093 | 31.0 | 23250 | 1.0694 | 0.9017 |
| 0.0 | 32.0 | 24000 | 1.0664 | 0.905 |
| 0.0036 | 33.0 | 24750 | 1.0692 | 0.8983 |
| 0.0002 | 34.0 | 25500 | 1.1060 | 0.8983 |
| 0.0035 | 35.0 | 26250 | 1.0709 | 0.8983 |
| 0.0001 | 36.0 | 27000 | 1.0498 | 0.9 |
| 0.0131 | 37.0 | 27750 | 1.0784 | 0.9083 |
| 0.0002 | 38.0 | 28500 | 1.0796 | 0.9033 |
| 0.0003 | 39.0 | 29250 | 1.0839 | 0.905 |
| 0.0001 | 40.0 | 30000 | 1.0780 | 0.905 |
| 0.0047 | 41.0 | 30750 | 1.0621 | 0.905 |
| 0.0001 | 42.0 | 31500 | 1.0644 | 0.9033 |
| 0.0003 | 43.0 | 32250 | 1.0821 | 0.905 |
| 0.0 | 44.0 | 33000 | 1.0754 | 0.9067 |
| 0.0161 | 45.0 | 33750 | 1.0831 | 0.905 |
| 0.0 | 46.0 | 34500 | 1.0684 | 0.905 |
| 0.0004 | 47.0 | 35250 | 1.0811 | 0.9017 |
| 0.0 | 48.0 | 36000 | 1.0871 | 0.9017 |
| 0.0045 | 49.0 | 36750 | 1.0895 | 0.905 |
| 0.0087 | 50.0 | 37500 | 1.0909 | 0.905 |
### Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0
- Datasets 2.14.6
- Tokenizers 0.14.1
| null | transformers | image-classification | null | null | null | null | null | null | null | null | null | onizukal/SMIDS_10x_beit_base_adamax_lr00001_fold4 | [
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mitchmartin/autocare | mitchmartin | 2023-11-29T07:08:56Z | 0 | 0 | null | [
"region:us"
] | 2023-11-29T07:08:56Z | 2023-11-29T07:06:18.000Z | null | null | Entry not found | null | null | null | null | null | null | null | null | null | null | null | null | mitchmartin/autocare | [
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hariduraibaskar/llama2_finetuned_sql | hariduraibaskar | 2023-11-29T15:16:28Z | 0 | 0 | null | [
"region:us"
] | 2023-11-29T15:16:28Z | 2023-11-29T07:07:47.000Z | null | null | Entry not found | null | null | null | null | null | null | null | null | null | null | null | null | hariduraibaskar/llama2_finetuned_sql | [
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LIGIONEERO/falcon_7b_chatbot | LIGIONEERO | 2023-11-29T07:08:55Z | 0 | 0 | null | [
"license:apache-2.0",
"region:us"
] | 2023-11-29T07:08:55Z | 2023-11-29T07:08:55.000Z | null | null | ---
license: apache-2.0
---
| null | null | null | null | null | null | null | null | null | null | null | null | LIGIONEERO/falcon_7b_chatbot | [
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dylan-demand-io/merged_model_mistral_tulu_ocr | dylan-demand-io | 2023-11-29T07:09:43Z | 0 | 0 | null | [
"region:us"
] | 2023-11-29T07:09:43Z | 2023-11-29T07:09:43.000Z | null | null | Entry not found | null | null | null | null | null | null | null | null | null | null | null | null | dylan-demand-io/merged_model_mistral_tulu_ocr | [
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nitzanb/mlm-heb-medical-b | nitzanb | 2023-11-29T08:35:25Z | 0 | 0 | null | [
"transformers",
"safetensors",
"bert",
"fill-mask",
"generated_from_trainer",
"base_model:imvladikon/alephbertgimmel-base-512",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | 2023-11-29T08:35:25Z | 2023-11-29T07:09:48.000Z | null | null | ---
base_model: imvladikon/alephbertgimmel-base-512
tags:
- generated_from_trainer
model-index:
- name: mlm-heb-medical-b
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. -->
# mlm-heb-medical-b
This model is a fine-tuned version of [imvladikon/alephbertgimmel-base-512](https://huggingface.co/imvladikon/alephbertgimmel-base-512) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8227
## 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:
- learning_rate: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.8563 | 1.0 | 8617 | 0.8177 |
### Framework versions
- Transformers 4.35.1
- Pytorch 2.0.1
- Datasets 2.15.0
- Tokenizers 0.14.1
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Rapando/KenyanConstitution | Rapando | 2023-11-29T07:13:27Z | 0 | 1 | null | [
"license:mit",
"region:us"
] | 2023-11-29T07:13:27Z | 2023-11-29T07:13:27.000Z | null | null | ---
license: mit
---
| null | null | null | null | null | null | null | null | null | null | null | null | Rapando/KenyanConstitution | [
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Realgon/t5_imdb_padding0model | Realgon | 2023-11-29T07:14:49Z | 0 | 0 | null | [
"region:us"
] | 2023-11-29T07:14:49Z | 2023-11-29T07:14:49.000Z | null | null | Entry not found | null | null | null | null | null | null | null | null | null | null | null | null | Realgon/t5_imdb_padding0model | [
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downquark/airoboros-l2-70b-3.1.2_exl_4.1bpw | downquark | 2023-11-29T07:15:15Z | 0 | 0 | null | [
"region:us"
] | 2023-11-29T07:15:15Z | 2023-11-29T07:15:15.000Z | null | null | Entry not found | null | null | null | null | null | null | null | null | null | null | null | null | downquark/airoboros-l2-70b-3.1.2_exl_4.1bpw | [
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sakgoyal/NLP_HW3 | sakgoyal | 2023-11-29T07:15:27Z | 0 | 0 | null | [
"region:us"
] | 2023-11-29T07:15:27Z | 2023-11-29T07:15:27.000Z | null | null | Entry not found | null | null | null | null | null | null | null | null | null | null | null | null | sakgoyal/NLP_HW3 | [
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mitchmartin/autohealth | mitchmartin | 2023-11-29T07:15:32Z | 0 | 0 | null | [
"region:us"
] | 2023-11-29T07:15:32Z | 2023-11-29T07:15:32.000Z | null | null | Entry not found | null | null | null | null | null | null | null | null | null | null | null | null | mitchmartin/autohealth | [
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