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---
library_name: transformers
license: apache-2.0
base_model: EleutherAI/pythia-14m-deduped
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: chennus-mini-2
  results: []
---

<!-- 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. -->

# mini-chennus-2

This model is a fine-tuned version of [EleutherAI/pythia-14m-deduped](https://huggingface.co/EleutherAI/pythia-14m-deduped) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: nan
- Accuracy: 0.0

## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- num_epochs: 6

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.0           | 0.1616 | 200  | nan             | 0.0      |
| 0.0           | 0.3231 | 400  | nan             | 0.0      |
| 0.0           | 0.4847 | 600  | nan             | 0.0      |
| 0.0           | 0.6462 | 800  | nan             | 0.0      |
| 0.0           | 0.8078 | 1000 | nan             | 0.0      |
| 0.0           | 0.9693 | 1200 | nan             | 0.0      |
| 0.0           | 1.1309 | 1400 | nan             | 0.0      |
| 0.0           | 1.2924 | 1600 | nan             | 0.0      |
| 0.0           | 1.4540 | 1800 | nan             | 0.0      |
| 0.0           | 1.6155 | 2000 | nan             | 0.0      |
| 0.0           | 1.7771 | 2200 | nan             | 0.0      |
| 0.0           | 1.9386 | 2400 | nan             | 0.0      |
| 0.0           | 2.1002 | 2600 | nan             | 0.0      |
| 0.0           | 2.2617 | 2800 | nan             | 0.0      |
| 0.0           | 2.4233 | 3000 | nan             | 0.0      |
| 0.0           | 2.5848 | 3200 | nan             | 0.0      |
| 0.0           | 2.7464 | 3400 | nan             | 0.0      |
| 0.0           | 2.9079 | 3600 | nan             | 0.0      |
| 0.0           | 3.0695 | 3800 | nan             | 0.0      |
| 0.0           | 3.2310 | 4000 | nan             | 0.0      |
| 0.0           | 3.3926 | 4200 | nan             | 0.0      |
| 0.0           | 3.5541 | 4400 | nan             | 0.0      |
| 0.0           | 3.7157 | 4600 | nan             | 0.0      |
| 0.0           | 3.8772 | 4800 | nan             | 0.0      |
| 0.0           | 4.0388 | 5000 | nan             | 0.0      |
| 0.0           | 4.2003 | 5200 | nan             | 0.0      |
| 0.0           | 4.3619 | 5400 | nan             | 0.0      |
| 0.0           | 4.5234 | 5600 | nan             | 0.0      |
| 0.0           | 4.6850 | 5800 | nan             | 0.0      |
| 0.0           | 4.8465 | 6000 | nan             | 0.0      |
| 0.0           | 5.0081 | 6200 | nan             | 0.0      |
| 0.0           | 5.1696 | 6400 | nan             | 0.0      |
| 0.0           | 5.3312 | 6600 | nan             | 0.0      |
| 0.0           | 5.4927 | 6800 | nan             | 0.0      |
| 0.0           | 5.6543 | 7000 | nan             | 0.0      |
| 0.0           | 5.8158 | 7200 | nan             | 0.0      |
| 0.0           | 5.9774 | 7400 | nan             | 0.0      |


### Framework versions

- Transformers 5.0.0
- Pytorch 2.10.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2