metadata
license: apache-2.0
base_model: pszemraj/mega-ar-350m-L3t-v0.07-cosmo_webmath_py
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: mega-ar-350m-L3t-v0.07-cosmo_webmath_py-UltraTextbooks-2.1-fw_mix-vN
results: []
mega-ar-350m-L3t-v0.07-cosmo_webmath_py-UltraTextbooks-2.1-fw_mix-vN
This model is a fine-tuned version of pszemraj/mega-ar-350m-L3t-v0.07-cosmo_webmath_py on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.0802
- Accuracy: 0.5744
- Num Input Tokens Seen: 3355443200
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: 4e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 80085
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 32
- total_train_batch_size: 128
- total_eval_batch_size: 4
- optimizer: Adam with betas=(0.9,0.98) and epsilon=1e-08
- lr_scheduler_type: inverse_sqrt
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 1.0
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | Input Tokens Seen |
---|---|---|---|---|---|
2.2572 | 0.0600 | 400 | 2.2462 | 0.5491 | 209715200 |
2.2173 | 0.1201 | 800 | 2.1939 | 0.5564 | 419430400 |
2.1992 | 0.1801 | 1200 | 2.1689 | 0.5604 | 629145600 |
2.1543 | 0.2402 | 1600 | 2.1521 | 0.5632 | 838860800 |
2.1532 | 0.3002 | 2000 | 2.1401 | 0.5650 | 1048576000 |
2.1688 | 0.3603 | 2400 | 2.1307 | 0.5663 | 1258291200 |
2.1443 | 0.4203 | 2800 | 2.1227 | 0.5676 | 1468006400 |
2.1105 | 0.4804 | 3200 | 2.1158 | 0.5689 | 1677721600 |
2.1045 | 0.5404 | 3600 | 2.1090 | 0.5700 | 1887436800 |
2.1181 | 0.6004 | 4000 | 2.1045 | 0.5708 | 2097152000 |
2.127 | 0.6605 | 4400 | 2.0994 | 0.5716 | 2306867200 |
2.1265 | 0.7205 | 4800 | 2.0958 | 0.5719 | 2516582400 |
2.0951 | 0.7806 | 5200 | 2.0909 | 0.5728 | 2726297600 |
2.0951 | 0.8406 | 5600 | 2.0876 | 0.5733 | 2936012800 |
2.1335 | 0.9007 | 6000 | 2.0838 | 0.5739 | 3145728000 |
2.0731 | 0.9607 | 6400 | 2.0802 | 0.5744 | 3355443200 |
Framework versions
- Transformers 4.40.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1