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---
tags:
- generated_from_trainer
datasets:
- kanishka/counterfactual-babylm-only_random_removal
metrics:
- accuracy
model-index:
- name: smolm-autoreg-bpe-counterfactual-babylm-only_random_removal-1e-3
results:
- task:
name: Causal Language Modeling
type: text-generation
dataset:
name: kanishka/counterfactual-babylm-only_random_removal
type: kanishka/counterfactual-babylm-only_random_removal
metrics:
- name: Accuracy
type: accuracy
value: 0.4103301921111753
---
<!-- 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-only_random_removal-1e-3
This model was trained from scratch on the kanishka/counterfactual-babylm-only_random_removal dataset.
It achieves the following results on the evaluation set:
- Loss: 3.4056
- Accuracy: 0.4103
## 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 |
|:-------------:|:-----:|:------:|:---------------:|:--------:|
| 3.6071 | 1.0 | 18588 | 3.7805 | 0.3590 |
| 3.3943 | 2.0 | 37176 | 3.5796 | 0.3806 |
| 3.2625 | 3.0 | 55764 | 3.4678 | 0.3915 |
| 3.1838 | 4.0 | 74352 | 3.3962 | 0.3998 |
| 3.1277 | 5.0 | 92940 | 3.3849 | 0.4017 |
| 3.0813 | 6.0 | 111528 | 3.3874 | 0.4040 |
| 3.0519 | 7.0 | 130116 | 3.3394 | 0.4079 |
| 3.0181 | 8.0 | 148704 | 3.3441 | 0.4085 |
| 2.9888 | 9.0 | 167292 | 3.3545 | 0.4088 |
| 2.9602 | 10.0 | 185880 | 3.3501 | 0.4088 |
| 2.942 | 11.0 | 204468 | 3.3509 | 0.4095 |
| 2.9174 | 12.0 | 223056 | 3.3709 | 0.4093 |
| 2.8989 | 13.0 | 241644 | 3.3608 | 0.4107 |
| 2.8757 | 14.0 | 260232 | 3.3651 | 0.4101 |
| 2.8506 | 15.0 | 278820 | 3.3638 | 0.4109 |
| 2.8373 | 16.0 | 297408 | 3.3724 | 0.4107 |
| 2.8195 | 17.0 | 315996 | 3.3819 | 0.4108 |
| 2.7983 | 18.0 | 334584 | 3.3819 | 0.4110 |
| 2.7786 | 19.0 | 353172 | 3.3970 | 0.4103 |
| 2.7635 | 20.0 | 371760 | 3.4056 | 0.4103 |
### Framework versions
- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1
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