---
tags:
- generated_from_trainer
datasets:
- kanishka/babylm2-subset
metrics:
- accuracy
model-index:
- name: opt-babylm2-subset-default-20-epochs-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: 0.5309790230016276
---

<!-- 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-20-epochs-3e-4

This model was trained from scratch on the kanishka/babylm2-subset dataset.
It achieves the following results on the evaluation set:
- Loss: 2.4374
- Accuracy: 0.5310

## 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: 20.0
- 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   |
| 2.2903        | 3.0   | 42507  | 2.5130          | 0.5119   |
| 2.2222        | 4.0   | 56676  | 2.4525          | 0.5194   |
| 2.1477        | 5.0   | 70845  | 2.4207          | 0.5237   |
| 2.0967        | 6.0   | 85014  | 2.3990          | 0.5266   |
| 2.0608        | 7.0   | 99183  | 2.3885          | 0.5284   |
| 2.0231        | 8.0   | 113352 | 2.3815          | 0.5296   |
| 1.9966        | 9.0   | 127521 | 2.3803          | 0.5304   |
| 1.974         | 10.0  | 141690 | 2.3802          | 0.5311   |
| 1.9469        | 11.0  | 155859 | 2.3798          | 0.5315   |
| 1.9241        | 12.0  | 170028 | 2.3857          | 0.5318   |
| 1.8975        | 13.0  | 184197 | 2.3908          | 0.5319   |
| 1.8763        | 14.0  | 198366 | 2.3943          | 0.5320   |
| 1.8519        | 15.0  | 212535 | 2.4029          | 0.5317   |
| 1.8306        | 16.0  | 226704 | 2.4098          | 0.5317   |
| 1.8045        | 17.0  | 240873 | 2.4174          | 0.5315   |
| 1.7801        | 18.0  | 255042 | 2.4237          | 0.5314   |
| 1.7649        | 19.0  | 269211 | 2.4308          | 0.5311   |
| 1.7481        | 20.0  | 283380 | 2.4374          | 0.5310   |


### Framework versions

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