---
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: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# 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](https://huggingface.co/pszemraj/mega-ar-350m-L3t-v0.07-cosmo_webmath_py) on the BEE-spoke-data/UltraTextbooks-2.1-fw_mix dataset.
It achieves the following results on the evaluation set:
- Loss: 2.0787
- Accuracy: 0.5746
- Num Input Tokens Seen: 3492282368

## 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