---
tags:
- generated_from_trainer
datasets:
- soda-clip-loader
model-index:
- name: soda-clip-finetuned
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# soda-clip-finetuned

This model was trained from scratch on the soda-clip-loader dataset.
It achieves the following results on the evaluation set:
- Loss: 1.9564

## 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: 128
- eval_batch_size: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5.0

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 4.6533        | 0.15  | 100  | 4.5663          |
| 4.5243        | 0.29  | 200  | 4.4131          |
| 4.2506        | 0.44  | 300  | 3.9908          |
| 3.9692        | 0.59  | 400  | 3.8105          |
| 3.7576        | 0.74  | 500  | 3.6515          |
| 3.5935        | 0.88  | 600  | 3.4758          |
| 3.3874        | 1.03  | 700  | 3.3259          |
| 3.1691        | 1.18  | 800  | 3.1645          |
| 3.021         | 1.33  | 900  | 3.0139          |
| 2.9045        | 1.47  | 1000 | 2.9027          |
| 2.8391        | 1.62  | 1100 | 2.8245          |
| 2.7293        | 1.77  | 1200 | 2.6703          |
| 2.6177        | 1.92  | 1300 | 2.5465          |
| 2.3473        | 2.06  | 1400 | 2.5076          |
| 2.1463        | 2.21  | 1500 | 2.4233          |
| 2.0842        | 2.36  | 1600 | 2.3488          |
| 2.0204        | 2.51  | 1700 | 2.2738          |
| 2.0013        | 2.65  | 1800 | 2.2473          |
| 1.9325        | 2.8   | 1900 | 2.2017          |
| 1.9072        | 2.95  | 2000 | 2.1397          |
| 1.5792        | 3.1   | 2100 | 2.1203          |
| 1.3949        | 3.24  | 2200 | 2.0973          |
| 1.3664        | 3.39  | 2300 | 2.0737          |
| 1.3545        | 3.54  | 2400 | 2.0320          |
| 1.3144        | 3.69  | 2500 | 2.0143          |
| 1.2897        | 3.83  | 2600 | 1.9552          |
| 1.2706        | 3.98  | 2700 | 1.9497          |
| 0.9014        | 4.13  | 2800 | 1.9983          |
| 0.8365        | 4.28  | 2900 | 1.9960          |
| 0.8187        | 4.42  | 3000 | 1.9886          |
| 0.8001        | 4.57  | 3100 | 1.9709          |
| 0.7979        | 4.72  | 3200 | 1.9513          |
| 0.7698        | 4.87  | 3300 | 1.9564          |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.2.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2