---
tags:
- generated_from_trainer
model-index:
- name: smol-finetuned-SC
  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. -->

# smol-finetuned-SC

This model was trained from scratch on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7200

## 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: 5
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 40
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| No log        | 0.0846 | 100  | 0.8014          |
| No log        | 0.1691 | 200  | 0.8304          |
| No log        | 0.2537 | 300  | 0.7394          |
| No log        | 0.3382 | 400  | 0.8970          |
| 0.7898        | 0.4228 | 500  | 0.7392          |
| 0.7898        | 0.5073 | 600  | 0.7310          |
| 0.7898        | 0.5919 | 700  | 0.8090          |
| 0.7898        | 0.6765 | 800  | 0.7245          |
| 0.7898        | 0.7610 | 900  | 0.7344          |
| 0.7284        | 0.8456 | 1000 | 0.7322          |
| 0.7284        | 0.9301 | 1100 | 0.7280          |
| 0.7284        | 1.0147 | 1200 | 0.7254          |
| 0.7284        | 1.0992 | 1300 | 0.7273          |
| 0.7284        | 1.1838 | 1400 | 0.7366          |
| 0.7173        | 1.2684 | 1500 | 0.7314          |
| 0.7173        | 1.3529 | 1600 | 0.7186          |
| 0.7173        | 1.4375 | 1700 | 0.7164          |
| 0.7173        | 1.5220 | 1800 | 0.7190          |
| 0.7173        | 1.6066 | 1900 | 0.7159          |
| 0.7196        | 1.6912 | 2000 | 0.7262          |
| 0.7196        | 1.7757 | 2100 | 0.7288          |
| 0.7196        | 1.8603 | 2200 | 0.7892          |
| 0.7196        | 1.9448 | 2300 | 0.7237          |
| 0.7196        | 2.0294 | 2400 | 0.7182          |
| 0.7166        | 2.1139 | 2500 | 0.7238          |
| 0.7166        | 2.1985 | 2600 | 0.7181          |
| 0.7166        | 2.2831 | 2700 | 0.7149          |
| 0.7166        | 2.3676 | 2800 | 0.7224          |
| 0.7166        | 2.4522 | 2900 | 0.7151          |
| 0.7047        | 2.5367 | 3000 | 0.7209          |
| 0.7047        | 2.6213 | 3100 | 0.7171          |
| 0.7047        | 2.7058 | 3200 | 0.7155          |
| 0.7047        | 2.7904 | 3300 | 0.7157          |
| 0.7047        | 2.8750 | 3400 | 0.7175          |
| 0.7081        | 2.9595 | 3500 | 0.7194          |
| 0.7081        | 3.0441 | 3600 | 0.7164          |
| 0.7081        | 3.1286 | 3700 | 0.7179          |
| 0.7081        | 3.2132 | 3800 | 0.7186          |
| 0.7081        | 3.2977 | 3900 | 0.7223          |
| 0.694         | 3.3823 | 4000 | 0.7195          |
| 0.694         | 3.4669 | 4100 | 0.7209          |
| 0.694         | 3.5514 | 4200 | 0.7181          |
| 0.694         | 3.6360 | 4300 | 0.7194          |
| 0.694         | 3.7205 | 4400 | 0.7184          |
| 0.6989        | 3.8051 | 4500 | 0.7203          |
| 0.6989        | 3.8897 | 4600 | 0.7192          |
| 0.6989        | 3.9742 | 4700 | 0.7200          |


### Framework versions

- Transformers 4.43.3
- Pytorch 2.1.0+cu118
- Datasets 2.14.5
- Tokenizers 0.19.1