---
tags:
- generated_from_trainer
datasets:
- kanishka/babylm2-subset
metrics:
- accuracy
model-index:
- name: cria-babylm2-subset-default-1e-3
  results:
  - task:
      name: Causal Language Modeling
      type: text-generation
    dataset:
      name: kanishka/babylm2-subset
      type: kanishka/babylm2-subset
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.5203706477236009
---

<!-- 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. -->

# cria-babylm2-subset-default-1e-3

This model was trained from scratch on the kanishka/babylm2-subset dataset.
It achieves the following results on the evaluation set:
- Loss: 2.6626
- Accuracy: 0.5204

## 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: 0.001
- train_batch_size: 32
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 32000
- num_epochs: 10.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step   | Validation Loss | Accuracy |
|:-------------:|:-----:|:------:|:---------------:|:--------:|
| 2.4397        | 1.0   | 14142  | 2.6684          | 0.4955   |
| 2.3085        | 2.0   | 28284  | 2.5420          | 0.5093   |
| 2.19          | 3.0   | 42426  | 2.4397          | 0.5215   |
| 2.0865        | 4.0   | 56568  | 2.3943          | 0.5276   |
| 1.9957        | 5.0   | 70710  | 2.3786          | 0.5305   |
| 1.9161        | 6.0   | 84852  | 2.3910          | 0.5313   |
| 1.8361        | 7.0   | 98994  | 2.4205          | 0.5304   |
| 1.7477        | 8.0   | 113136 | 2.4748          | 0.5283   |
| 1.6549        | 9.0   | 127278 | 2.5582          | 0.5249   |
| 1.5611        | 10.0  | 141420 | 2.6626          | 0.5204   |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.2.0+cu121
- Datasets 2.16.1
- Tokenizers 0.19.1