---
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: 4.8565

## 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: 0.0001
- 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 4.8557        | 0.15  | 100  | 4.8520          |
| 4.852         | 0.29  | 200  | 4.8520          |
| 4.8526        | 0.44  | 300  | 4.8522          |
| 4.8521        | 0.59  | 400  | 4.8520          |
| 4.852         | 0.74  | 500  | 4.8520          |
| 4.852         | 0.88  | 600  | 4.8520          |
| 4.852         | 1.03  | 700  | 4.8520          |
| 4.8519        | 1.18  | 800  | 4.8542          |
| 4.8522        | 1.33  | 900  | 4.8520          |
| 4.852         | 1.47  | 1000 | 4.8520          |
| 4.852         | 1.62  | 1100 | 4.8520          |
| 4.852         | 1.77  | 1200 | 4.8520          |
| 4.852         | 1.92  | 1300 | 4.8520          |
| 4.852         | 2.06  | 1400 | 4.8520          |
| 4.852         | 2.21  | 1500 | 4.8520          |
| 4.852         | 2.36  | 1600 | 4.8520          |
| 4.852         | 2.51  | 1700 | 4.8520          |
| 4.852         | 2.65  | 1800 | 4.8520          |
| 4.852         | 2.8   | 1900 | 4.8520          |
| 4.852         | 2.95  | 2000 | 4.8522          |
| 4.852         | 3.1   | 2100 | 4.8521          |
| 4.852         | 3.24  | 2200 | 4.8521          |
| 4.8519        | 3.39  | 2300 | 4.8523          |
| 4.8521        | 3.54  | 2400 | 4.8521          |
| 4.852         | 3.69  | 2500 | 4.8521          |
| 4.8517        | 3.83  | 2600 | 4.8521          |
| 4.852         | 3.98  | 2700 | 4.8520          |
| 4.852         | 4.13  | 2800 | 4.8520          |
| 4.852         | 4.28  | 2900 | 4.8520          |
| 4.852         | 4.42  | 3000 | 4.8520          |
| 4.8519        | 4.57  | 3100 | 4.8523          |
| 4.8515        | 4.72  | 3200 | 4.8528          |
| 4.851         | 4.87  | 3300 | 4.8565          |


### Framework versions

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