File size: 3,197 Bytes
47f963e a12ac6a 47f963e a12ac6a 47f963e a12ac6a 47f963e |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 |
---
tags:
- generated_from_trainer
datasets:
- kanishka/counterfactual-babylm-only_indef_articles_with_pl_nouns_removal
metrics:
- accuracy
model-index:
- name: smolm-autoreg-bpe-counterfactual-babylm-only_indef_articles_with_pl_nouns_removal-seed_1024-1e-3
results:
- task:
name: Causal Language Modeling
type: text-generation
dataset:
name: kanishka/counterfactual-babylm-only_indef_articles_with_pl_nouns_removal
type: kanishka/counterfactual-babylm-only_indef_articles_with_pl_nouns_removal
metrics:
- name: Accuracy
type: accuracy
value: 0.41096838506284816
---
<!-- 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_indef_articles_with_pl_nouns_removal-seed_1024-1e-3
This model was trained from scratch on the kanishka/counterfactual-babylm-only_indef_articles_with_pl_nouns_removal dataset.
It achieves the following results on the evaluation set:
- Loss: 3.4006
- Accuracy: 0.4110
## 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: 1024
- 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 |
|:-------------:|:-----:|:------:|:---------------:|:--------:|
| 3.6013 | 1.0 | 18600 | 3.7573 | 0.3598 |
| 3.3813 | 2.0 | 37200 | 3.5688 | 0.3805 |
| 3.2541 | 3.0 | 55800 | 3.4489 | 0.3922 |
| 3.174 | 4.0 | 74400 | 3.4158 | 0.3980 |
| 3.1166 | 5.0 | 93000 | 3.3767 | 0.4028 |
| 3.0777 | 6.0 | 111600 | 3.3729 | 0.4036 |
| 3.0372 | 7.0 | 130200 | 3.3464 | 0.4071 |
| 3.0083 | 8.0 | 148800 | 3.3503 | 0.4081 |
| 2.9762 | 9.0 | 167400 | 3.3317 | 0.4098 |
| 2.9515 | 10.0 | 186000 | 3.3434 | 0.4088 |
| 2.9338 | 11.0 | 204600 | 3.3526 | 0.4102 |
| 2.9063 | 12.0 | 223200 | 3.3577 | 0.4095 |
| 2.8871 | 13.0 | 241800 | 3.3493 | 0.4101 |
| 2.8654 | 14.0 | 260400 | 3.3641 | 0.4106 |
| 2.8465 | 15.0 | 279000 | 3.3597 | 0.4115 |
| 2.8233 | 16.0 | 297600 | 3.3748 | 0.4106 |
| 2.8071 | 17.0 | 316200 | 3.3754 | 0.4113 |
| 2.7899 | 18.0 | 334800 | 3.3833 | 0.4111 |
| 2.7669 | 19.0 | 353400 | 3.3913 | 0.4112 |
| 2.7513 | 20.0 | 372000 | 3.4006 | 0.4110 |
### Framework versions
- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1
|