---
tags:
- generated_from_trainer
datasets:
- soda-panelized-clip-loader
model-index:
- name: soda-clip
  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

This model was trained from scratch on the soda-panelized-clip-loader dataset.
It achieves the following results on the evaluation set:
- Loss: 1.9732

## 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: 64
- eval_batch_size: 64
- 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 4.0258        | 0.13  | 100  | 3.7622          |
| 3.556         | 0.26  | 200  | 3.4317          |
| 3.3307        | 0.39  | 300  | 3.2219          |
| 3.2305        | 0.51  | 400  | 3.1044          |
| 3.1104        | 0.64  | 500  | 2.9733          |
| 2.9966        | 0.77  | 600  | 2.8562          |
| 2.8576        | 0.9   | 700  | 2.8080          |
| 2.7558        | 1.03  | 800  | 2.6612          |
| 2.5565        | 1.16  | 900  | 2.6441          |
| 2.4791        | 1.28  | 1000 | 2.5369          |
| 2.4483        | 1.41  | 1100 | 2.4951          |
| 2.3751        | 1.54  | 1200 | 2.3893          |
| 2.3408        | 1.67  | 1300 | 2.3960          |
| 2.2761        | 1.8   | 1400 | 2.2943          |
| 2.2426        | 1.93  | 1500 | 2.2422          |
| 2.0389        | 2.05  | 1600 | 2.2475          |
| 1.8415        | 2.18  | 1700 | 2.1555          |
| 1.8286        | 2.31  | 1800 | 2.1755          |
| 1.7927        | 2.44  | 1900 | 2.1267          |
| 1.7693        | 2.57  | 2000 | 2.0621          |
| 1.7448        | 2.7   | 2100 | 2.0653          |
| 1.7027        | 2.82  | 2200 | 2.0110          |
| 1.7184        | 2.95  | 2300 | 1.9699          |
| 1.4059        | 3.08  | 2400 | 1.9781          |
| 1.2499        | 3.21  | 2500 | 1.9837          |
| 1.2478        | 3.34  | 2600 | 1.9859          |
| 1.1903        | 3.47  | 2700 | 1.9470          |
| 1.1989        | 3.59  | 2800 | 1.9819          |
| 1.169         | 3.72  | 2900 | 1.9825          |
| 1.1538        | 3.85  | 3000 | 1.9429          |
| 1.1178        | 3.98  | 3100 | 1.9387          |
| 0.8271        | 4.11  | 3200 | 1.9931          |
| 0.748         | 4.24  | 3300 | 1.9974          |
| 0.7123        | 4.36  | 3400 | 1.9994          |
| 0.7012        | 4.49  | 3500 | 1.9967          |
| 0.7163        | 4.62  | 3600 | 1.9914          |
| 0.6899        | 4.75  | 3700 | 1.9836          |
| 0.6608        | 4.88  | 3800 | 1.9732          |


### Framework versions

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