
<!-- 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-aann-indef-non_num_removal-1e-4

This model was trained from scratch on the kanishka/counterfactual-babylm-aanns_indef_non_num_removal dataset.
It achieves the following results on the evaluation set:
- Loss: 3.4253
- Accuracy: 0.4052

## 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: 0.0001
- 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 |
|:-------------:|:-----:|:------:|:---------------:|:--------:|
| 4.0479        | 1.0   | 18592  | 4.2707          | 0.3092   |
| 3.5639        | 2.0   | 37184  | 3.7423          | 0.3625   |
| 3.3891        | 3.0   | 55776  | 3.5886          | 0.3789   |
| 3.2863        | 4.0   | 74368  | 3.4958          | 0.3879   |
| 3.2196        | 5.0   | 92960  | 3.4607          | 0.3931   |
| 3.1627        | 6.0   | 111552 | 3.4520          | 0.3956   |
| 3.1282        | 7.0   | 130144 | 3.4094          | 0.3982   |
| 3.0897        | 8.0   | 148736 | 3.4137          | 0.3995   |
| 3.0631        | 9.0   | 167328 | 3.4069          | 0.4010   |
| 3.0316        | 10.0  | 185920 | 3.4121          | 0.4018   |
| 3.0154        | 11.0  | 204512 | 3.4134          | 0.4020   |
| 2.9887        | 12.0  | 223104 | 3.4061          | 0.4032   |
| 2.9637        | 13.0  | 241696 | 3.4075          | 0.4038   |
| 2.9493        | 14.0  | 260288 | 3.4058          | 0.4045   |
| 2.9268        | 15.0  | 278880 | 3.4043          | 0.4047   |
| 2.9095        | 16.0  | 297472 | 3.4192          | 0.4048   |
| 2.8912        | 17.0  | 316064 | 3.4116          | 0.4050   |
| 2.875         | 18.0  | 334656 | 3.4216          | 0.4049   |
| 2.8542        | 19.0  | 353248 | 3.4266          | 0.4052   |
| 2.8429        | 20.0  | 371840 | 3.4253          | 0.4052   |


### 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-aanns_indef_non_num_removal"], "metrics": ["accuracy"], "model-index": [{"name": "smolm-autoreg-bpe-counterfactual-babylm-aann-indef-non_num_removal-1e-4", "results": [{"task": {"type": "text-generation", "name": "Causal Language Modeling"}, "dataset": {"name": "kanishka/counterfactual-babylm-aanns_indef_non_num_removal", "type": "kanishka/counterfactual-babylm-aanns_indef_non_num_removal"}, "metrics": [{"type": "accuracy", "value": 0.4052309408152, "name": "Accuracy"}]}]}]}
transformers safetensors opt text-generation generated_from_trainer dataset:kanishka/counterfactual-babylm-aanns_indef_non_num_removal model-index autotrain_compatible endpoints_compatible text-generation-inference region:us