---
tags:
- generated_from_trainer
datasets:
- kanishka/babylm2-subset
metrics:
- accuracy
model-index:
- name: opt-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: 0.534805757971141
---

<!-- 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-1e-3

This model was trained from scratch on the kanishka/babylm2-subset dataset.
It achieves the following results on the evaluation set:
- Loss: 2.3689
- Accuracy: 0.5348

## 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 |
|:-------------:|:-----:|:------:|:---------------:|:--------:|
| 2.5477        | 1.0   | 14142  | 2.7490          | 0.4855   |
| 2.377         | 2.0   | 28284  | 2.5803          | 0.5045   |
| 2.2625        | 3.0   | 42426  | 2.4760          | 0.5164   |
| 2.1715        | 4.0   | 56568  | 2.4206          | 0.5235   |
| 2.0996        | 5.0   | 70710  | 2.3880          | 0.5278   |
| 2.0456        | 6.0   | 84852  | 2.3722          | 0.5306   |
| 1.9983        | 7.0   | 98994  | 2.3592          | 0.5327   |
| 1.9482        | 8.0   | 113136 | 2.3579          | 0.5338   |
| 1.9061        | 9.0   | 127278 | 2.3605          | 0.5346   |
| 1.8692        | 10.0  | 141420 | 2.3689          | 0.5348   |


### Framework versions

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