---
library_name: transformers
tags:
- generated_from_trainer
datasets:
- kanishka/babylm2-clean-spacy
metrics:
- accuracy
model-index:
- name: opt-babylm2-clean-spacy-32k_seed-42_1e-3
  results:
  - task:
      name: Causal Language Modeling
      type: text-generation
    dataset:
      name: kanishka/babylm2-clean-spacy
      type: kanishka/babylm2-clean-spacy
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.4232865945768086
---

<!-- 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-clean-spacy-32k_seed-42_1e-3

This model was trained from scratch on the kanishka/babylm2-clean-spacy dataset.
It achieves the following results on the evaluation set:
- Loss: 3.0380
- Accuracy: 0.4233

## 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: 20.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step   | Validation Loss | Accuracy |
|:-------------:|:-----:|:------:|:---------------:|:--------:|
| 3.26          | 1.0   | 15543  | 3.3136          | 0.3831   |
| 3.0629        | 2.0   | 31086  | 3.1530          | 0.3996   |
| 2.9355        | 3.0   | 46629  | 3.0425          | 0.4114   |
| 2.8499        | 4.0   | 62172  | 2.9935          | 0.4172   |
| 2.7951        | 5.0   | 77715  | 2.9681          | 0.4207   |
| 2.7489        | 6.0   | 93258  | 2.9527          | 0.4226   |
| 2.7031        | 7.0   | 108801 | 2.9438          | 0.4242   |
| 2.6642        | 8.0   | 124344 | 2.9425          | 0.4251   |
| 2.6242        | 9.0   | 139887 | 2.9441          | 0.4255   |
| 2.5991        | 10.0  | 155430 | 2.9460          | 0.4258   |
| 2.5731        | 11.0  | 170973 | 2.9496          | 0.4259   |
| 2.5387        | 12.0  | 186516 | 2.9571          | 0.4259   |
| 2.5106        | 13.0  | 202059 | 2.9727          | 0.4256   |
| 2.4846        | 14.0  | 217602 | 2.9750          | 0.4257   |
| 2.4638        | 15.0  | 233145 | 2.9852          | 0.4250   |
| 2.4351        | 16.0  | 248688 | 2.9968          | 0.4247   |
| 2.4119        | 17.0  | 264231 | 3.0044          | 0.4244   |
| 2.3894        | 18.0  | 279774 | 3.0132          | 0.4241   |
| 2.3569        | 19.0  | 295317 | 3.0270          | 0.4237   |
| 2.3375        | 20.0  | 310860 | 3.0380          | 0.4233   |


### Framework versions

- Transformers 4.45.1
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.0