Instructions to use SaladSlayer00/image_classification_resnet with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SaladSlayer00/image_classification_resnet with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="SaladSlayer00/image_classification_resnet") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("SaladSlayer00/image_classification_resnet") model = AutoModelForImageClassification.from_pretrained("SaladSlayer00/image_classification_resnet", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit ·
c86795d
1
Parent(s): bb2ecc3
Training in progress epoch 6
Browse files
README.md
CHANGED
|
@@ -15,10 +15,10 @@ probably proofread and complete it, then remove this comment. -->
|
|
| 15 |
|
| 16 |
This model is a fine-tuned version of [microsoft/resnet-50](https://huggingface.co/microsoft/resnet-50) on an unknown dataset.
|
| 17 |
It achieves the following results on the evaluation set:
|
| 18 |
-
- Train Loss: 2.
|
| 19 |
-
- Validation Loss: 2.
|
| 20 |
-
- Validation Accuracy: 0.
|
| 21 |
-
- Epoch:
|
| 22 |
|
| 23 |
## Model description
|
| 24 |
|
|
@@ -50,6 +50,7 @@ The following hyperparameters were used during training:
|
|
| 50 |
| 3.8826 | 3.6814 | 0.1758 | 3 |
|
| 51 |
| 3.4086 | 3.2561 | 0.2531 | 4 |
|
| 52 |
| 2.9790 | 2.8971 | 0.3091 | 5 |
|
|
|
|
| 53 |
|
| 54 |
|
| 55 |
### Framework versions
|
|
|
|
| 15 |
|
| 16 |
This model is a fine-tuned version of [microsoft/resnet-50](https://huggingface.co/microsoft/resnet-50) on an unknown dataset.
|
| 17 |
It achieves the following results on the evaluation set:
|
| 18 |
+
- Train Loss: 2.5850
|
| 19 |
+
- Validation Loss: 2.5861
|
| 20 |
+
- Validation Accuracy: 0.3718
|
| 21 |
+
- Epoch: 6
|
| 22 |
|
| 23 |
## Model description
|
| 24 |
|
|
|
|
| 50 |
| 3.8826 | 3.6814 | 0.1758 | 3 |
|
| 51 |
| 3.4086 | 3.2561 | 0.2531 | 4 |
|
| 52 |
| 2.9790 | 2.8971 | 0.3091 | 5 |
|
| 53 |
+
| 2.5850 | 2.5861 | 0.3718 | 6 |
|
| 54 |
|
| 55 |
|
| 56 |
### Framework versions
|
logs/train/events.out.tfevents.1703538427.fv-az847-406.1850.0.v2
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
-
size
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:5e1fc57b733574c617a70e6e6b67619a07f166fcf6301fd98f4b07ec830e96e0
|
| 3 |
+
size 1400675
|
logs/validation/events.out.tfevents.1703540000.fv-az847-406.1850.1.v2
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
-
size
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:9cabd1e1b63fd16666b930798f40bbbd89dbabd9538da22a626f2ec35515951a
|
| 3 |
+
size 1670
|
tf_model.h5
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 167707244
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:0d6a82a2a2fdd255470ae732708b5d3529199c4d63bce899cdb6aa17b86799b5
|
| 3 |
size 167707244
|