---
tags:
- generated_from_trainer
datasets:
- kanishka/babylm2-subset
metrics:
- accuracy
model-index:
- name: opt-babylm2-subset-default-3e-4
  results:
  - task:
      name: Causal Language Modeling
      type: text-generation
    dataset:
      name: kanishka/babylm2-subset
      type: kanishka/babylm2-subset
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.5327396962492645
---

<!-- 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. -->

# opt-babylm2-subset-default-3e-4

This model was trained from scratch on the kanishka/babylm2-subset dataset.
It achieves the following results on the evaluation set:
- Loss: 2.3776
- Accuracy: 0.5327

## 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: 0.0003
- 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 |
|:-------------:|:-----:|:------:|:---------------:|:--------:|
| 2.6575        | 1.0   | 14169  | 2.8571          | 0.4750   |
| 2.4179        | 2.0   | 28338  | 2.6258          | 0.4990   |
| 2.286         | 3.0   | 42507  | 2.5088          | 0.5123   |
| 2.2124        | 4.0   | 56676  | 2.4448          | 0.5203   |
| 2.1307        | 5.0   | 70845  | 2.4099          | 0.5251   |
| 2.0706        | 6.0   | 85014  | 2.3887          | 0.5281   |
| 2.0233        | 7.0   | 99183  | 2.3779          | 0.5304   |
| 1.9727        | 8.0   | 113352 | 2.3731          | 0.5315   |
| 1.9311        | 9.0   | 127521 | 2.3728          | 0.5324   |
| 1.8943        | 10.0  | 141690 | 2.3776          | 0.5327   |


### Framework versions

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