transformers safetensors opt text-generation generated_from_trainer dataset:kanishka/counterfactual_babylm_aann_indef_naan model-index autotrain_compatible endpoints_compatible text-generation-inference region:us
---
tags:
- generated_from_trainer
datasets:
- kanishka/counterfactual_babylm_aann_indef_naan
metrics:
- accuracy
model-index:
- name: smolm-autoreg-bpe-counterfactual-babylm-indef-naan-rerun-1e-3
  results:
  - task:
      name: Causal Language Modeling
      type: text-generation
    dataset:
      name: kanishka/counterfactual_babylm_aann_indef_naan
      type: kanishka/counterfactual_babylm_aann_indef_naan
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.41192589100799243
---

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# smolm-autoreg-bpe-counterfactual-babylm-indef-naan-rerun-1e-3

This model was trained from scratch on the kanishka/counterfactual_babylm_aann_indef_naan dataset.
It achieves the following results on the evaluation set:
- Loss: 3.3895
- Accuracy: 0.4119

## 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 |
|:-------------:|:-----:|:------:|:---------------:|:--------:|
| 3.6029        | 1.0   | 18595  | 3.7537          | 0.3598   |
| 3.3802        | 2.0   | 37190  | 3.5615          | 0.3808   |
| 3.2525        | 3.0   | 55785  | 3.4488          | 0.3937   |
| 3.1763        | 4.0   | 74380  | 3.4286          | 0.3985   |
| 3.1225        | 5.0   | 92975  | 3.3738          | 0.4026   |
| 3.0759        | 6.0   | 111570 | 3.3256          | 0.4086   |
| 3.039         | 7.0   | 130165 | 3.3437          | 0.4070   |
| 3.0127        | 8.0   | 148760 | 3.3430          | 0.4087   |
| 2.9832        | 9.0   | 167355 | 3.3458          | 0.4102   |
| 2.9576        | 10.0  | 185950 | 3.3349          | 0.4113   |
| 2.9308        | 11.0  | 204545 | 3.3456          | 0.4117   |
| 2.9111        | 12.0  | 223140 | 3.3457          | 0.4114   |
| 2.8929        | 13.0  | 241735 | 3.3436          | 0.4124   |
| 2.872         | 14.0  | 260330 | 3.3454          | 0.4122   |
| 2.8466        | 15.0  | 278925 | 3.3455          | 0.4130   |
| 2.8309        | 16.0  | 297520 | 3.3553          | 0.4125   |
| 2.81          | 17.0  | 316115 | 3.3644          | 0.4124   |
| 2.7893        | 18.0  | 334710 | 3.3733          | 0.4124   |
| 2.775         | 19.0  | 353305 | 3.3852          | 0.4119   |
| 2.7548        | 20.0  | 371900 | 3.3895          | 0.4119   |


### Framework versions

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