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---
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: smolm-autoreg-bpe-counterfactual-babylm-pipps-random_removal-seed_211-1e-3
results: []
---
<!-- 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-pipps-random_removal-seed_211-1e-3
This model was trained from scratch on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 3.4120
- Accuracy: 0.4099
## 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: 211
- 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 |
|:-------------:|:-----:|:------:|:---------------:|:--------:|
| 3.6072 | 1.0 | 18592 | 3.7972 | 0.3577 |
| 3.3863 | 2.0 | 37184 | 3.5804 | 0.3804 |
| 3.2556 | 3.0 | 55776 | 3.4730 | 0.3910 |
| 3.1829 | 4.0 | 74368 | 3.4019 | 0.3992 |
| 3.1264 | 5.0 | 92960 | 3.3828 | 0.4020 |
| 3.0827 | 6.0 | 111552 | 3.3849 | 0.4031 |
| 3.0461 | 7.0 | 130144 | 3.3728 | 0.4050 |
| 3.0111 | 8.0 | 148736 | 3.3609 | 0.4069 |
| 2.9857 | 9.0 | 167328 | 3.3496 | 0.4082 |
| 2.9608 | 10.0 | 185920 | 3.3683 | 0.4075 |
| 2.9402 | 11.0 | 204512 | 3.3728 | 0.4086 |
| 2.9154 | 12.0 | 223104 | 3.3845 | 0.4083 |
| 2.891 | 13.0 | 241696 | 3.3741 | 0.4098 |
| 2.8754 | 14.0 | 260288 | 3.3674 | 0.4106 |
| 2.8555 | 15.0 | 278880 | 3.3868 | 0.4095 |
| 2.8368 | 16.0 | 297472 | 3.3892 | 0.4098 |
| 2.8185 | 17.0 | 316064 | 3.3865 | 0.4106 |
| 2.7969 | 18.0 | 334656 | 3.4006 | 0.4099 |
| 2.7805 | 19.0 | 353248 | 3.3997 | 0.4104 |
| 2.7623 | 20.0 | 371840 | 3.4120 | 0.4099 |
### Framework versions
- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1
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