File size: 2,888 Bytes
1698099 4c9d28a 1698099 4c9d28a 1698099 4c9d28a 1698099 |
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/babylm2-subset
metrics:
- accuracy
model-index:
- name: opt-babylm2-subset-default-20-epochs-1e-3
results:
- task:
name: Causal Language Modeling
type: text-generation
dataset:
name: kanishka/babylm2-subset
type: kanishka/babylm2-subset
metrics:
- name: Accuracy
type: accuracy
value: 0.5324464855196746
---
<!-- 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. -->
# opt-babylm2-subset-default-20-epochs-1e-3
This model was trained from scratch on the kanishka/babylm2-subset dataset.
It achieves the following results on the evaluation set:
- Loss: 2.4350
- Accuracy: 0.5324
## 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 |
|:-------------:|:-----:|:------:|:---------------:|:--------:|
| 2.5365 | 1.0 | 14169 | 2.7500 | 0.4857 |
| 2.3708 | 2.0 | 28338 | 2.5870 | 0.5032 |
| 2.2572 | 3.0 | 42507 | 2.4839 | 0.5150 |
| 2.1958 | 4.0 | 56676 | 2.4295 | 0.5220 |
| 2.1251 | 5.0 | 70845 | 2.4013 | 0.5259 |
| 2.0769 | 6.0 | 85014 | 2.3830 | 0.5281 |
| 2.043 | 7.0 | 99183 | 2.3736 | 0.5304 |
| 2.007 | 8.0 | 113352 | 2.3671 | 0.5313 |
| 1.9813 | 9.0 | 127521 | 2.3661 | 0.5322 |
| 1.9593 | 10.0 | 141690 | 2.3705 | 0.5325 |
| 1.933 | 11.0 | 155859 | 2.3677 | 0.5331 |
| 1.9106 | 12.0 | 170028 | 2.3727 | 0.5333 |
| 1.8847 | 13.0 | 184197 | 2.3779 | 0.5335 |
| 1.8636 | 14.0 | 198366 | 2.3834 | 0.5335 |
| 1.8391 | 15.0 | 212535 | 2.3955 | 0.5334 |
| 1.8179 | 16.0 | 226704 | 2.4015 | 0.5332 |
| 1.7918 | 17.0 | 240873 | 2.4100 | 0.5331 |
| 1.7674 | 18.0 | 255042 | 2.4159 | 0.5330 |
| 1.751 | 19.0 | 269211 | 2.4263 | 0.5327 |
| 1.7338 | 20.0 | 283380 | 2.4350 | 0.5324 |
### Framework versions
- Transformers 4.42.4
- Pytorch 2.2.0+cu121
- Datasets 2.16.1
- Tokenizers 0.19.1
|