---
base_model: models/smolm-mlm/config.json
tags:
- generated_from_trainer
datasets:
  - AO-CHILDES
metrics:
- accuracy
widget:
  - text: Do you like your <mask> ?
  - text: Look here . What is that <mask> ?
  - text: Where is <mask> ?
model-index:
- name: smolm-mlm-bpe-unmask-seed_111
  results: []
pipeline_tag: fill-mask
---

<!-- 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. -->

# smolm-mlm-bpe-unmask-seed_111

This model is a fine-tuned version of [models/smolm-mlm/config.json](https://huggingface.co/models/smolm-mlm/config.json) on 5M words of American-English child-directed input.
It achieves the following results on the evaluation set:
- Loss: 2.6956
- Accuracy: 0.4492

## 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: 0.0005
- train_batch_size: 64
- eval_batch_size: 512
- seed: 111
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 24000
- num_epochs: 10.0

### Training results

| Training Loss | Epoch | Step   | Validation Loss | Accuracy |
|:-------------:|:-----:|:------:|:---------------:|:--------:|
| 3.5129        | 1.0   | 11938  | 3.4627          | 0.3523   |
| 3.319         | 2.0   | 23876  | 3.3322          | 0.3641   |
| 3.1577        | 3.0   | 35814  | 3.1841          | 0.3810   |
| 3.0357        | 4.0   | 47752  | 3.0588          | 0.3982   |
| 2.9606        | 5.0   | 59690  | 2.9535          | 0.4109   |
| 2.87          | 6.0   | 71628  | 2.8745          | 0.4221   |
| 2.7817        | 7.0   | 83566  | 2.8351          | 0.4284   |
| 2.7388        | 8.0   | 95504  | 2.7536          | 0.4417   |
| 2.6618        | 9.0   | 107442 | 2.7308          | 0.4424   |
| 2.6258        | 10.0  | 119380 | 2.6880          | 0.4522   |


### Framework versions

- Transformers 4.32.1
- Pytorch 1.13.1+cu117
- Datasets 2.12.0
- Tokenizers 0.13.3