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# smolm-autoreg-bpe-counterfactual-babylm-all_det_removal-1e-3

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: 3.3747
- Accuracy: 0.4145

## 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: 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 |
|:-------------:|:-----:|:------:|:---------------:|:--------:|
| 3.5047        | 1.0   | 37189  | 3.6845          | 0.3698   |
| 3.3066        | 2.0   | 74378  | 3.5029          | 0.3916   |
| 3.2057        | 3.0   | 111567 | 3.4215          | 0.4009   |
| 3.1465        | 4.0   | 148756 | 3.3806          | 0.4041   |
| 3.0913        | 5.0   | 185945 | 3.3560          | 0.4080   |
| 3.0564        | 6.0   | 223134 | 3.3460          | 0.4096   |
| 3.0166        | 7.0   | 260323 | 3.3310          | 0.4121   |
| 2.992         | 8.0   | 297512 | 3.3089          | 0.4140   |
| 2.9737        | 9.0   | 334701 | 3.3280          | 0.4140   |
| 2.9434        | 10.0  | 371890 | 3.3233          | 0.4137   |
| 2.9163        | 11.0  | 409079 | 3.3369          | 0.4129   |
| 2.8966        | 12.0  | 446268 | 3.3243          | 0.4140   |
| 2.8708        | 13.0  | 483457 | 3.3356          | 0.4142   |
| 2.8526        | 14.0  | 520646 | 3.3450          | 0.4131   |
| 2.8321        | 15.0  | 557835 | 3.3447          | 0.4133   |
| 2.8124        | 16.0  | 595024 | 3.3455          | 0.4148   |
| 2.798         | 17.0  | 632213 | 3.3559          | 0.4150   |
| 2.7737        | 18.0  | 669402 | 3.3648          | 0.4140   |
| 2.7557        | 19.0  | 706591 | 3.3696          | 0.4146   |
| 2.7432        | 20.0  | 743780 | 3.3747          | 0.4145   |


### 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-1e-3", "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": 0.41452023342272576, "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