
<!-- 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. -->

# smolm-autoreg-bpe-counterfactual-babylm-all_det_removal-3e-4

This model was trained from scratch on the kanishka/counterfactual_babylm_aann_all_det_removal dataset.
It achieves the following results on the evaluation set:
- Loss: 3.4401
- Accuracy: 0.4087

## 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: 16
- 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 |
|:-------------:|:-----:|:------:|:---------------:|:--------:|
| 3.5638        | 1.0   | 37189  | 3.7368          | 0.3622   |
| 3.3412        | 2.0   | 74378  | 3.5511          | 0.3852   |
| 3.2337        | 3.0   | 111567 | 3.4790          | 0.3939   |
| 3.1708        | 4.0   | 148756 | 3.4317          | 0.3994   |
| 3.1125        | 5.0   | 185945 | 3.4199          | 0.4013   |
| 3.0765        | 6.0   | 223134 | 3.4033          | 0.4038   |
| 3.0361        | 7.0   | 260323 | 3.3774          | 0.4055   |
| 3.0108        | 8.0   | 297512 | 3.3853          | 0.4064   |
| 2.9931        | 9.0   | 334701 | 3.3719          | 0.4072   |
| 2.9628        | 10.0  | 371890 | 3.3715          | 0.4079   |
| 2.9363        | 11.0  | 409079 | 3.3925          | 0.4082   |
| 2.9167        | 12.0  | 446268 | 3.3869          | 0.4083   |
| 2.8918        | 13.0  | 483457 | 3.3873          | 0.4089   |
| 2.8737        | 14.0  | 520646 | 3.3924          | 0.4086   |
| 2.8545        | 15.0  | 557835 | 3.3917          | 0.4090   |
| 2.8353        | 16.0  | 595024 | 3.4101          | 0.4089   |
| 2.8209        | 17.0  | 632213 | 3.4230          | 0.4089   |
| 2.7977        | 18.0  | 669402 | 3.4256          | 0.4089   |
| 2.781         | 19.0  | 706591 | 3.4295          | 0.4089   |
| 2.7692        | 20.0  | 743780 | 3.4401          | 0.4087   |


### Framework versions

- Transformers 4.36.0
- Pytorch 2.1.1+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0

{"tags": ["generated_from_trainer"], "datasets": ["kanishka/counterfactual_babylm_aann_all_det_removal"], "metrics": ["accuracy"], "model-index": [{"name": "smolm-autoreg-bpe-counterfactual-babylm-all_det_removal-3e-4", "results": [{"task": {"type": "text-generation", "name": "Causal Language Modeling"}, "dataset": {"name": "kanishka/counterfactual_babylm_aann_all_det_removal", "type": "kanishka/counterfactual_babylm_aann_all_det_removal"}, "metrics": [{"type": "accuracy", "value": 0.40870703690431515, "name": "Accuracy"}]}]}]}
transformers safetensors opt text-generation generated_from_trainer dataset:kanishka/counterfactual_babylm_aann_all_det_removal model-index autotrain_compatible endpoints_compatible text-generation-inference region:us