Upload folder using huggingface_hub
Browse files- README-template.md +95 -0
- README.md +95 -0
- metadata.json +8 -0
- model.safetensors +3 -0
- optimizer.pt +3 -0
- rng_state.pth +3 -0
- scheduler.pt +3 -0
- trainer_state.json +611 -0
- training_args.bin +3 -0
README-template.md
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| 1 |
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---
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license: apache-2.0
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base_model: google/vit-base-patch16-224
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tags:
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- Image Regression
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| 6 |
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datasets:
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- "-"
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| 8 |
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metrics:
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| 9 |
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- accuracy
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| 10 |
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model-index:
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- name: "-"
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results: []
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| 13 |
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---
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| 14 |
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| 15 |
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# Title
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| 16 |
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## Image Regression Model
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| 17 |
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| 18 |
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This model was trained with [Image Regression Model Trainer](https://github.com/TonyAssi/ImageRegression/tree/main). It takes an image as input and outputs a float value.
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| 19 |
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```python
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from ImageRegression import predict
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predict(repo_id='-',image_path='image.jpg')
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```
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---
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## Dataset
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Dataset:\
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Value Column:\
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| 30 |
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Train Test Split:
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| 31 |
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---
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| 33 |
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| 34 |
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## Training
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| 35 |
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Base Model: [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224)\
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| 36 |
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Epochs:\
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| 37 |
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Learning Rate:
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| 38 |
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| 39 |
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---
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| 40 |
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## Usage
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| 42 |
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| 43 |
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### Download
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| 44 |
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```bash
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git clone https://github.com/TonyAssi/ImageRegression.git
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cd ImageRegression
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```
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| 48 |
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+
### Installation
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| 50 |
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```bash
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pip install -r requirements.txt
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```
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### Import
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| 55 |
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```python
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from ImageRegression import train_model, upload_model, predict
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| 57 |
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```
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| 58 |
+
|
| 59 |
+
### Inference (Prediction)
|
| 60 |
+
- **repo_id** 🤗 repo id of the model
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| 61 |
+
- **image_path** path to image
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| 62 |
+
```python
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| 63 |
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predict(repo_id='-',
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| 64 |
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image_path='image.jpg')
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| 65 |
+
```
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| 66 |
+
The first time this function is called it'll download the safetensor model. Subsequent function calls will run faster.
|
| 67 |
+
|
| 68 |
+
### Train Model
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| 69 |
+
- **dataset_id** 🤗 dataset id
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| 70 |
+
- **value_column_name** column name of prediction values in dataset
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| 71 |
+
- **test_split** test split of the train/test split
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| 72 |
+
- **output_dir** the directory where the checkpoints will be saved
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| 73 |
+
- **num_train_epochs** training epochs
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| 74 |
+
- **learning_rate** learning rate
|
| 75 |
+
```python
|
| 76 |
+
train_model(dataset_id='-',
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| 77 |
+
value_column_name='-',
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| 78 |
+
test_split=-,
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| 79 |
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output_dir='./results',
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| 80 |
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num_train_epochs=-,
|
| 81 |
+
learning_rate=-)
|
| 82 |
+
|
| 83 |
+
```
|
| 84 |
+
The trainer will save the checkpoints in the output_dir location. The model.safetensors are the trained weights you'll use for inference (predicton).
|
| 85 |
+
|
| 86 |
+
### Upload Model
|
| 87 |
+
This function will upload your model to the 🤗 Hub.
|
| 88 |
+
- **model_id** the name of the model id
|
| 89 |
+
- **token** go [here](https://huggingface.co/settings/tokens) to create a new 🤗 token
|
| 90 |
+
- **checkpoint_dir** checkpoint folder that will be uploaded
|
| 91 |
+
```python
|
| 92 |
+
upload_model(model_id='-',
|
| 93 |
+
token='YOUR_HF_TOKEN',
|
| 94 |
+
checkpoint_dir='./results/checkpoint-940')
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| 95 |
+
```
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README.md
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| 1 |
+
---
|
| 2 |
+
license: apache-2.0
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| 3 |
+
base_model: google/vit-base-patch16-224
|
| 4 |
+
tags:
|
| 5 |
+
- Image Regression
|
| 6 |
+
datasets:
|
| 7 |
+
- "Popipopi93/bottle_finder"
|
| 8 |
+
metrics:
|
| 9 |
+
- accuracy
|
| 10 |
+
model-index:
|
| 11 |
+
- name: "model_colab_20_bis"
|
| 12 |
+
results: []
|
| 13 |
+
---
|
| 14 |
+
|
| 15 |
+
# model_colab_20_bis
|
| 16 |
+
## Image Regression Model
|
| 17 |
+
|
| 18 |
+
This model was trained with [Image Regression Model Trainer](https://github.com/TonyAssi/ImageRegression/tree/main). It takes an image as input and outputs a float value.
|
| 19 |
+
|
| 20 |
+
```python
|
| 21 |
+
from ImageRegression import predict
|
| 22 |
+
predict(repo_id='Popipopi93/model_colab_20_bis',image_path='image.jpg')
|
| 23 |
+
```
|
| 24 |
+
|
| 25 |
+
---
|
| 26 |
+
|
| 27 |
+
## Dataset
|
| 28 |
+
Dataset: Popipopi93/bottle_finder\
|
| 29 |
+
Value Column: 'level'\
|
| 30 |
+
Train Test Split: 0.1
|
| 31 |
+
|
| 32 |
+
---
|
| 33 |
+
|
| 34 |
+
## Training
|
| 35 |
+
Base Model: [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224)\
|
| 36 |
+
Epochs: 20\
|
| 37 |
+
Learning Rate: 0.0001
|
| 38 |
+
|
| 39 |
+
---
|
| 40 |
+
|
| 41 |
+
## Usage
|
| 42 |
+
|
| 43 |
+
### Download
|
| 44 |
+
```bash
|
| 45 |
+
git clone https://github.com/TonyAssi/ImageRegression.git
|
| 46 |
+
cd ImageRegression
|
| 47 |
+
```
|
| 48 |
+
|
| 49 |
+
### Installation
|
| 50 |
+
```bash
|
| 51 |
+
pip install -r requirements.txt
|
| 52 |
+
```
|
| 53 |
+
|
| 54 |
+
### Import
|
| 55 |
+
```python
|
| 56 |
+
from ImageRegression import train_model, upload_model, predict
|
| 57 |
+
```
|
| 58 |
+
|
| 59 |
+
### Inference (Prediction)
|
| 60 |
+
- **repo_id** 🤗 repo id of the model
|
| 61 |
+
- **image_path** path to image
|
| 62 |
+
```python
|
| 63 |
+
predict(repo_id='Popipopi93/model_colab_20_bis',
|
| 64 |
+
image_path='image.jpg')
|
| 65 |
+
```
|
| 66 |
+
The first time this function is called it'll download the safetensor model. Subsequent function calls will run faster.
|
| 67 |
+
|
| 68 |
+
### Train Model
|
| 69 |
+
- **dataset_id** 🤗 dataset id
|
| 70 |
+
- **value_column_name** column name of prediction values in dataset
|
| 71 |
+
- **test_split** test split of the train/test split
|
| 72 |
+
- **output_dir** the directory where the checkpoints will be saved
|
| 73 |
+
- **num_train_epochs** training epochs
|
| 74 |
+
- **learning_rate** learning rate
|
| 75 |
+
```python
|
| 76 |
+
train_model(dataset_id='Popipopi93/bottle_finder',
|
| 77 |
+
value_column_name='level',
|
| 78 |
+
test_split=0.1,
|
| 79 |
+
output_dir='./results',
|
| 80 |
+
num_train_epochs=20,
|
| 81 |
+
learning_rate=0.0001)
|
| 82 |
+
|
| 83 |
+
```
|
| 84 |
+
The trainer will save the checkpoints in the output_dir location. The model.safetensors are the trained weights you'll use for inference (predicton).
|
| 85 |
+
|
| 86 |
+
### Upload Model
|
| 87 |
+
This function will upload your model to the 🤗 Hub.
|
| 88 |
+
- **model_id** the name of the model id
|
| 89 |
+
- **token** go [here](https://huggingface.co/settings/tokens) to create a new 🤗 token
|
| 90 |
+
- **checkpoint_dir** checkpoint folder that will be uploaded
|
| 91 |
+
```python
|
| 92 |
+
upload_model(model_id='model_colab_20_bis',
|
| 93 |
+
token='YOUR_HF_TOKEN',
|
| 94 |
+
checkpoint_dir='./results/checkpoint-940')
|
| 95 |
+
```
|
metadata.json
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{
|
| 2 |
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"dataset_id": "Popipopi93/bottle_finder",
|
| 3 |
+
"value_column_name": "level",
|
| 4 |
+
"test_split": 0.1,
|
| 5 |
+
"num_train_epochs": 20,
|
| 6 |
+
"learning_rate": 0.0001,
|
| 7 |
+
"max_value": 1.0
|
| 8 |
+
}
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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| 2 |
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oid sha256:5779d24e8ada28193263577cce44f8ebaa0cdc473edb1f03fac9598de9e7ce98
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| 3 |
+
size 345583444
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optimizer.pt
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version https://git-lfs.github.com/spec/v1
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oid sha256:66202774450a90a2018b51401996dd5da972086797d026eebc5871b567690edb
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| 3 |
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size 686562746
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rng_state.pth
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version https://git-lfs.github.com/spec/v1
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| 2 |
+
oid sha256:289fef051795377d49c655aebabbd2a059abf20869cd8ff3db6589fc9191aaf7
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| 3 |
+
size 14244
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scheduler.pt
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version https://git-lfs.github.com/spec/v1
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| 2 |
+
oid sha256:5c3e81fd065498afdffbac649d956b8dfda003ccf6ce8894b8c036e844497086
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| 3 |
+
size 1064
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trainer_state.json
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"learning_rate": 6.666666666666667e-05,
|
| 586 |
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"loss": 0.0006,
|
| 587 |
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"step": 400
|
| 588 |
+
}
|
| 589 |
+
],
|
| 590 |
+
"logging_steps": 10,
|
| 591 |
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"max_steps": 1200,
|
| 592 |
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"num_input_tokens_seen": 0,
|
| 593 |
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"num_train_epochs": 100,
|
| 594 |
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"save_steps": 10,
|
| 595 |
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"stateful_callbacks": {
|
| 596 |
+
"TrainerControl": {
|
| 597 |
+
"args": {
|
| 598 |
+
"should_epoch_stop": false,
|
| 599 |
+
"should_evaluate": false,
|
| 600 |
+
"should_log": false,
|
| 601 |
+
"should_save": true,
|
| 602 |
+
"should_training_stop": false
|
| 603 |
+
},
|
| 604 |
+
"attributes": {}
|
| 605 |
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}
|
| 606 |
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},
|
| 607 |
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"total_flos": 0.0,
|
| 608 |
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"train_batch_size": 8,
|
| 609 |
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"trial_name": null,
|
| 610 |
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"trial_params": null
|
| 611 |
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}
|
training_args.bin
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:2a4dba23053dac499d8d450e9b5f3e36297a28b03ccf516e82dff9469a0f364e
|
| 3 |
+
size 5304
|