---
library_name: transformers
tags:
- generated_from_trainer
datasets:
- kanishka/babylm2-clean-spacy
metrics:
- accuracy
model-index:
- name: opt-babylm2-clean-spacy-32k_seed-42_3e-4
  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: 0.4234014597448438
---

<!-- 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_3e-4

This model was trained from scratch on the kanishka/babylm2-clean-spacy dataset.
It achieves the following results on the evaluation set:
- Loss: 3.0190
- Accuracy: 0.4234

## 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 |
|:-------------:|:-----:|:------:|:---------------:|:--------:|
| 3.3944        | 1.0   | 15543  | 3.4212          | 0.3734   |
| 3.1245        | 2.0   | 31086  | 3.2037          | 0.3940   |
| 2.9807        | 3.0   | 46629  | 3.0794          | 0.4073   |
| 2.8872        | 4.0   | 62172  | 3.0205          | 0.4140   |
| 2.8286        | 5.0   | 77715  | 2.9885          | 0.4180   |
| 2.779         | 6.0   | 93258  | 2.9699          | 0.4206   |
| 2.7316        | 7.0   | 108801 | 2.9588          | 0.4222   |
| 2.6909        | 8.0   | 124344 | 2.9554          | 0.4233   |
| 2.6504        | 9.0   | 139887 | 2.9544          | 0.4238   |
| 2.6246        | 10.0  | 155430 | 2.9523          | 0.4244   |
| 2.5988        | 11.0  | 170973 | 2.9568          | 0.4248   |
| 2.5639        | 12.0  | 186516 | 2.9595          | 0.4248   |
| 2.5361        | 13.0  | 202059 | 2.9698          | 0.4248   |
| 2.5098        | 14.0  | 217602 | 2.9747          | 0.4247   |
| 2.4899        | 15.0  | 233145 | 2.9792          | 0.4247   |
| 2.4626        | 16.0  | 248688 | 2.9882          | 0.4244   |
| 2.4399        | 17.0  | 264231 | 2.9961          | 0.4243   |
| 2.4186        | 18.0  | 279774 | 3.0051          | 0.4239   |
| 2.3869        | 19.0  | 295317 | 3.0119          | 0.4237   |
| 2.3686        | 20.0  | 310860 | 3.0190          | 0.4234   |


### Framework versions

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