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# convnext_manuscript_iiif

This model is a fine-tuned version of [facebook/convnext-base-224-22k](https://huggingface.co/facebook/convnext-base-224-22k) on the davanstrien/iiif_manuscripts_label_ge_50 dataset.
It achieves the following results on the evaluation set:
- Loss: 5.5856
- F1: 0.0037

## 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: 64
- eval_batch_size: 64
- seed: 1337
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | F1     |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 6.5753        | 1.0   | 2038  | 6.4121          | 0.0016 |
| 5.9865        | 2.0   | 4076  | 5.9466          | 0.0021 |
| 5.6521        | 3.0   | 6114  | 5.7645          | 0.0029 |
| 5.3123        | 4.0   | 8152  | 5.6890          | 0.0033 |
| 5.0337        | 5.0   | 10190 | 5.6692          | 0.0034 |
| 4.743         | 6.0   | 12228 | 5.5856          | 0.0037 |
| 4.4387        | 7.0   | 14266 | 5.5969          | 0.0042 |
| 4.1422        | 8.0   | 16304 | 5.6711          | 0.0043 |
| 3.8372        | 9.0   | 18342 | 5.6761          | 0.0044 |
| 3.5244        | 10.0  | 20380 | 5.8469          | 0.0042 |
| 3.2321        | 11.0  | 22418 | 5.8774          | 0.0045 |
| 2.9004        | 12.0  | 24456 | 6.1186          | 0.0047 |
| 2.5937        | 13.0  | 26494 | 6.2398          | 0.0046 |
| 2.2983        | 14.0  | 28532 | 6.3732          | 0.0049 |
| 2.0611        | 15.0  | 30570 | 6.5024          | 0.0045 |
| 1.8153        | 16.0  | 32608 | 6.6585          | 0.0047 |
| 1.6075        | 17.0  | 34646 | 6.8333          | 0.0043 |
| 1.4342        | 18.0  | 36684 | 6.9529          | 0.0044 |
| 1.2614        | 19.0  | 38722 | 7.1129          | 0.0046 |
| 1.1463        | 20.0  | 40760 | 7.1977          | 0.0039 |
| 1.0387        | 21.0  | 42798 | 7.2700          | 0.0044 |
| 0.9635        | 22.0  | 44836 | 7.3375          | 0.0040 |
| 0.8872        | 23.0  | 46874 | 7.4003          | 0.0039 |
| 0.8156        | 24.0  | 48912 | 7.4884          | 0.0039 |
| 0.7544        | 25.0  | 50950 | 7.4764          | 0.0039 |
| 0.6893        | 26.0  | 52988 | 7.5153          | 0.0042 |
| 0.6767        | 27.0  | 55026 | 7.5427          | 0.0043 |
| 0.6098        | 28.0  | 57064 | 7.5547          | 0.0042 |
| 0.5871        | 29.0  | 59102 | 7.5533          | 0.0041 |
| 0.5696        | 30.0  | 61140 | 7.5595          | 0.0041 |


### Framework versions

- Transformers 4.18.0.dev0
- Pytorch 1.10.2+cu102
- Datasets 1.18.3
- Tokenizers 0.11.6

{"license": "apache-2.0", "tags": ["image-classification", "generated_from_trainer"], "metrics": ["f1"], "base_model": "facebook/convnext-base-224-22k", "model-index": [{"name": "convnext_manuscript_iiif", "results": []}]}
transformers pytorch safetensors convnext image-classification generated_from_trainer base_model:facebook/convnext-base-224-22k license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #safetensors #convnext #image-classification #generated_from_trainer #base_model-facebook/convnext-base-224-22k #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 

convnext\_manuscript\_iiif
==========================


This model is a fine-tuned version of facebook/convnext-base-224-22k on the davanstrien/iiif\_manuscripts\_label\_ge\_50 dataset.
It achieves the following results on the evaluation set:


* Loss: 5.5856
* F1: 0.0037


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: 64
* eval\_batch\_size: 64
* seed: 1337
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 30.0
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.18.0.dev0
* Pytorch 1.10.2+cu102
* Datasets 1.18.3
* Tokenizers 0.11.6



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0002
* train\_batch\_size: 64
* eval\_batch\_size: 64
* seed: 1337
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 30.0
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.18.0.dev0
* Pytorch 1.10.2+cu102
* Datasets 1.18.3
* Tokenizers 0.11.6
TAGS
#transformers #pytorch #safetensors #convnext #image-classification #generated_from_trainer #base_model-facebook/convnext-base-224-22k #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0002
* train\_batch\_size: 64
* eval\_batch\_size: 64
* seed: 1337
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 30.0
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.18.0.dev0
* Pytorch 1.10.2+cu102
* Datasets 1.18.3
* Tokenizers 0.11.6
passage: TAGS
#transformers #pytorch #safetensors #convnext #image-classification #generated_from_trainer #base_model-facebook/convnext-base-224-22k #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0002
* train\_batch\_size: 64
* eval\_batch\_size: 64
* seed: 1337
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 30.0
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.18.0.dev0
* Pytorch 1.10.2+cu102
* Datasets 1.18.3
* Tokenizers 0.11.6