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---
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: smolm-autoreg-bpe-counterfactual-babylm-indef-removal-seed_211-1e-4
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-indef-removal-seed_211-1e-4
This model was trained from scratch on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 3.4163
- Accuracy: 0.4076
## 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: 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 |
|:-------------:|:-----:|:------:|:---------------:|:--------:|
| 4.0497 | 1.0 | 18595 | 4.2852 | 0.3080 |
| 3.565 | 2.0 | 37190 | 3.7283 | 0.3633 |
| 3.3896 | 3.0 | 55785 | 3.5917 | 0.3804 |
| 3.2893 | 4.0 | 74380 | 3.5098 | 0.3893 |
| 3.2194 | 5.0 | 92975 | 3.4496 | 0.3948 |
| 3.1724 | 6.0 | 111570 | 3.4233 | 0.3982 |
| 3.1258 | 7.0 | 130165 | 3.4181 | 0.4005 |
| 3.0958 | 8.0 | 148760 | 3.4253 | 0.4011 |
| 3.0662 | 9.0 | 167355 | 3.4222 | 0.4023 |
| 3.0368 | 10.0 | 185950 | 3.4052 | 0.4037 |
| 3.0083 | 11.0 | 204545 | 3.3978 | 0.4047 |
| 2.9889 | 12.0 | 223140 | 3.3996 | 0.4056 |
| 2.9622 | 13.0 | 241735 | 3.3896 | 0.4065 |
| 2.9419 | 14.0 | 260330 | 3.3847 | 0.4072 |
| 2.9292 | 15.0 | 278925 | 3.4022 | 0.4065 |
| 2.9096 | 16.0 | 297520 | 3.4086 | 0.4071 |
| 2.893 | 17.0 | 316115 | 3.4042 | 0.4074 |
| 2.872 | 18.0 | 334710 | 3.4126 | 0.4074 |
| 2.8563 | 19.0 | 353305 | 3.4111 | 0.4076 |
| 2.8424 | 20.0 | 371900 | 3.4163 | 0.4076 |
### Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0+cu121
- Datasets 2.12.0
- Tokenizers 0.14.1
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