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# cord-classif-model

This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2013
- Accuracy: 1.0

## 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
- gradient_accumulation_steps: 2
- total_train_batch_size: 4
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 8

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.7042        | 0.1111 | 1    | 0.6871          | 0.5      |
| 0.7058        | 0.2222 | 2    | 0.6750          | 0.6      |
| 0.6416        | 0.3333 | 3    | 0.6667          | 0.9      |
| 0.6936        | 0.4444 | 4    | 0.6343          | 0.7      |
| 0.6629        | 0.5556 | 5    | 0.6190          | 0.9      |
| 0.7195        | 0.6667 | 6    | 0.5947          | 0.9      |
| 0.6868        | 0.7778 | 7    | 0.6155          | 0.9      |
| 0.6476        | 0.8889 | 8    | 0.5540          | 0.9      |
| 0.7552        | 1.0    | 9    | 0.5931          | 0.9      |
| 0.5168        | 1.1111 | 10   | 0.5694          | 0.9      |
| 0.4808        | 1.2222 | 11   | 0.5690          | 0.9      |
| 0.6157        | 1.3333 | 12   | 0.5573          | 0.9      |
| 0.5479        | 1.4444 | 13   | 0.5512          | 0.9      |
| 0.4646        | 1.5556 | 14   | 0.5307          | 0.9      |
| 0.4772        | 1.6667 | 15   | 0.5170          | 0.9      |
| 0.4864        | 1.7778 | 16   | 0.5357          | 0.9      |
| 0.4775        | 1.8889 | 17   | 0.4613          | 0.9      |
| 0.6061        | 2.0    | 18   | 0.4886          | 0.9      |
| 0.3524        | 2.1111 | 19   | 0.4830          | 0.9      |
| 0.3927        | 2.2222 | 20   | 0.4916          | 0.9      |
| 0.4264        | 2.3333 | 21   | 0.4799          | 0.9      |
| 0.3172        | 2.4444 | 22   | 0.4445          | 0.9      |
| 0.3645        | 2.5556 | 23   | 0.4737          | 0.9      |
| 0.3675        | 2.6667 | 24   | 0.4502          | 0.9      |
| 0.5295        | 2.7778 | 25   | 0.4212          | 0.9      |
| 0.2749        | 2.8889 | 26   | 0.4278          | 0.9      |
| 0.3156        | 3.0    | 27   | 0.4320          | 0.9      |
| 0.3443        | 3.1111 | 28   | 0.3981          | 0.9      |
| 0.3151        | 3.2222 | 29   | 0.3999          | 0.9      |
| 0.3343        | 3.3333 | 30   | 0.3813          | 0.9      |
| 0.2849        | 3.4444 | 31   | 0.3708          | 0.9      |
| 0.203         | 3.5556 | 32   | 0.3883          | 0.9      |
| 0.2974        | 3.6667 | 33   | 0.3516          | 0.9      |
| 0.39          | 3.7778 | 34   | 0.3712          | 0.9      |
| 0.3439        | 3.8889 | 35   | 0.3459          | 0.9      |
| 0.311         | 4.0    | 36   | 0.3271          | 0.9      |
| 0.2814        | 4.1111 | 37   | 0.3801          | 0.9      |
| 0.161         | 4.2222 | 38   | 0.3165          | 0.9      |
| 0.14          | 4.3333 | 39   | 0.2890          | 0.9      |
| 0.3928        | 4.4444 | 40   | 0.3259          | 0.9      |
| 0.1812        | 4.5556 | 41   | 0.2839          | 0.9      |
| 0.21          | 4.6667 | 42   | 0.2612          | 1.0      |
| 0.1424        | 4.7778 | 43   | 0.3312          | 1.0      |
| 0.2238        | 4.8889 | 44   | 0.2660          | 0.9      |
| 0.2472        | 5.0    | 45   | 0.2653          | 0.9      |
| 0.1143        | 5.1111 | 46   | 0.2353          | 1.0      |
| 0.1888        | 5.2222 | 47   | 0.2542          | 1.0      |
| 0.2183        | 5.3333 | 48   | 0.2679          | 1.0      |
| 0.1019        | 5.4444 | 49   | 0.2618          | 1.0      |
| 0.2266        | 5.5556 | 50   | 0.2353          | 1.0      |
| 0.15          | 5.6667 | 51   | 0.2337          | 1.0      |
| 0.2253        | 5.7778 | 52   | 0.2540          | 1.0      |
| 0.1451        | 5.8889 | 53   | 0.2390          | 1.0      |
| 0.1481        | 6.0    | 54   | 0.2346          | 0.9      |
| 0.1112        | 6.1111 | 55   | 0.2171          | 1.0      |
| 0.1482        | 6.2222 | 56   | 0.2044          | 1.0      |
| 0.181         | 6.3333 | 57   | 0.1914          | 1.0      |
| 0.1091        | 6.4444 | 58   | 0.1911          | 1.0      |
| 0.1205        | 6.5556 | 59   | 0.1990          | 1.0      |
| 0.16          | 6.6667 | 60   | 0.1984          | 1.0      |
| 0.0967        | 6.7778 | 61   | 0.1852          | 1.0      |
| 0.1812        | 6.8889 | 62   | 0.1976          | 1.0      |
| 0.1711        | 7.0    | 63   | 0.1766          | 1.0      |
| 0.1959        | 7.1111 | 64   | 0.2000          | 1.0      |
| 0.4228        | 7.2222 | 65   | 0.2017          | 1.0      |
| 0.506         | 7.3333 | 66   | 0.1828          | 1.0      |
| 0.1869        | 7.4444 | 67   | 0.1728          | 1.0      |
| 0.0914        | 7.5556 | 68   | 0.1846          | 1.0      |
| 0.1622        | 7.6667 | 69   | 0.2005          | 1.0      |
| 0.0884        | 7.7778 | 70   | 0.2367          | 1.0      |
| 0.1018        | 7.8889 | 71   | 0.1785          | 1.0      |
| 0.1132        | 8.0    | 72   | 0.2013          | 1.0      |


### Framework versions

- Transformers 4.48.3
- Pytorch 2.6.0+cpu
- Datasets 3.2.0
- Tokenizers 0.21.0

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