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# finetune-clip-vit-large-patch14

This model is a fine-tuned version of [openai/clip-vit-large-patch14](https://huggingface.co/openai/clip-vit-large-patch14) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6545
- F1: 0.6242

## 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: 32
- 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
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | F1     |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 0.7084        | 0.3690 | 100  | 0.7173          | 0.5405 |
| 0.6818        | 0.7380 | 200  | 0.7269          | 0.5683 |
| 0.7169        | 1.1070 | 300  | 0.6949          | 0.5683 |
| 0.6957        | 1.4760 | 400  | 0.6799          | 0.5650 |
| 0.6218        | 1.8450 | 500  | 0.7344          | 0.5766 |
| 0.6406        | 2.2140 | 600  | 0.6600          | 0.6118 |
| 0.6645        | 2.5830 | 700  | 0.6581          | 0.6113 |
| 0.6546        | 2.9520 | 800  | 0.6549          | 0.6192 |
| 0.6068        | 3.3210 | 900  | 0.6542          | 0.6224 |
| 0.6351        | 3.6900 | 1000 | 0.6545          | 0.6242 |


### Framework versions

- Transformers 4.45.1
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.20.0

not-sarcasm sarcasm