metadata
tags:
- generated_from_trainer
datasets:
- kanishka/counterfactual_babylm_anans_new
metrics:
- accuracy
model-index:
- name: smolm-autoreg-bpe-counterfactual_babylm_anans_new-1e-4
results:
- task:
name: Causal Language Modeling
type: text-generation
dataset:
name: kanishka/counterfactual_babylm_anans_new
type: kanishka/counterfactual_babylm_anans_new
metrics:
- name: Accuracy
type: accuracy
value: 0.4074434673767711
smolm-autoreg-bpe-counterfactual_babylm_anans_new-1e-4
This model was trained from scratch on the kanishka/counterfactual_babylm_anans_new dataset. It achieves the following results on the evaluation set:
- Loss: 3.4007
- Accuracy: 0.4074
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: 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 |
|---|---|---|---|---|
| 4.0511 | 1.0 | 18595 | 4.2394 | 0.3093 |
| 3.5633 | 2.0 | 37190 | 3.7416 | 0.3637 |
| 3.3921 | 3.0 | 55785 | 3.5710 | 0.3807 |
| 3.2853 | 4.0 | 74380 | 3.5125 | 0.3883 |
| 3.2219 | 5.0 | 92975 | 3.4521 | 0.3931 |
| 3.1716 | 6.0 | 111570 | 3.4476 | 0.3967 |
| 3.1281 | 7.0 | 130165 | 3.4214 | 0.3994 |
| 3.0951 | 8.0 | 148760 | 3.4083 | 0.4018 |
| 3.0631 | 9.0 | 167355 | 3.3979 | 0.4024 |
| 3.0407 | 10.0 | 185950 | 3.3901 | 0.4042 |
| 3.0103 | 11.0 | 204545 | 3.3945 | 0.4041 |
| 2.9879 | 12.0 | 223140 | 3.3859 | 0.4055 |
| 2.9716 | 13.0 | 241735 | 3.3779 | 0.4063 |
| 2.9449 | 14.0 | 260330 | 3.3843 | 0.4066 |
| 2.9277 | 15.0 | 278925 | 3.3808 | 0.4074 |
| 2.9087 | 16.0 | 297520 | 3.3866 | 0.4070 |
| 2.8913 | 17.0 | 316115 | 3.3875 | 0.4071 |
| 2.8771 | 18.0 | 334710 | 3.3993 | 0.4071 |
| 2.8633 | 19.0 | 353305 | 3.3992 | 0.4073 |
| 2.8505 | 20.0 | 371900 | 3.4007 | 0.4074 |
Framework versions
- Transformers 4.40.1
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.19.1