metadata
tags:
- generated_from_trainer
datasets:
- kanishka/counterfactual_babylm_aann_dtanns
metrics:
- accuracy
model-index:
- name: smolm-autoreg-bpe-counterfactual_babylm_aanns_dtanns-seed_211-1e-4
results:
- task:
name: Causal Language Modeling
type: text-generation
dataset:
name: kanishka/counterfactual_babylm_aann_dtanns
type: kanishka/counterfactual_babylm_aann_dtanns
metrics:
- name: Accuracy
type: accuracy
value: 0.40547080986496004
smolm-autoreg-bpe-counterfactual_babylm_aanns_dtanns-seed_211-1e-4
This model was trained from scratch on the kanishka/counterfactual_babylm_aann_dtanns dataset. It achieves the following results on the evaluation set:
- Loss: 3.4323
- Accuracy: 0.4055
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 |
|---|---|---|---|---|
| 4.0524 | 1.0 | 18595 | 4.2811 | 0.3084 |
| 3.5716 | 2.0 | 37190 | 3.7750 | 0.3615 |
| 3.3913 | 3.0 | 55785 | 3.6008 | 0.3779 |
| 3.2921 | 4.0 | 74380 | 3.5102 | 0.3883 |
| 3.2283 | 5.0 | 92975 | 3.4789 | 0.3930 |
| 3.1673 | 6.0 | 111570 | 3.4379 | 0.3962 |
| 3.127 | 7.0 | 130165 | 3.4175 | 0.3988 |
| 3.0935 | 8.0 | 148760 | 3.4272 | 0.3998 |
| 3.0679 | 9.0 | 167355 | 3.4150 | 0.4011 |
| 3.0402 | 10.0 | 185950 | 3.4148 | 0.4023 |
| 3.0082 | 11.0 | 204545 | 3.4169 | 0.4029 |
| 2.988 | 12.0 | 223140 | 3.4130 | 0.4035 |
| 2.967 | 13.0 | 241735 | 3.3969 | 0.4045 |
| 2.9457 | 14.0 | 260330 | 3.4080 | 0.4049 |
| 2.9268 | 15.0 | 278925 | 3.4129 | 0.4045 |
| 2.911 | 16.0 | 297520 | 3.4159 | 0.4047 |
| 2.8964 | 17.0 | 316115 | 3.4221 | 0.4051 |
| 2.8758 | 18.0 | 334710 | 3.4286 | 0.4054 |
| 2.858 | 19.0 | 353305 | 3.4265 | 0.4054 |
| 2.8493 | 20.0 | 371900 | 3.4323 | 0.4055 |
Framework versions
- Transformers 4.38.0
- Pytorch 2.3.1+cu121
- Datasets 2.16.1
- Tokenizers 0.15.2